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880 | 1 | Learning reactive robot behaviors with Neural-Q_leaning The purpose of this paper is to propose a Neural-Q_learning approach designed for online learning of simple and reactive robot behaviors. In this approach, the Q_function is generalized by a multi-layer neural network allowing the use of continuous states and actions. The algorithm uses a database of the most recent learning samples to accelerate and guarantee the convergence. Each Neural-Q_learning function represents an independent, reactive and adaptive behavior which maps sensorial states to robot control actions. A group of these behaviors constitutes a reactive control scheme designed to fulfill simple missions. The paper centers on the description of the Neural-Q_learning based behaviors showing their performance with an autonomous underwater vehicle (AUV) in a target following mission. Simulated experiments demonstrate the convergence and stability of the learning system, pointing out its suitability for online robot learning. Advantages and limitations are discussed. | [
470
] | Train |
881 | 0 | Towards Flexible Multi-Agent Decision-Making Under Time Pressure Abstract — Autonomous agents need considerable computational resources to perform rational decision-making. These demands are even more severe when other agents are present in the environment. In these settings, the quality of an agent’s alternative behaviors depends not only on the state of the environment, but also on the actions of other agents, which in turn depend on the others ’ beliefs about the world, their preferences, and further on the other agents’ beliefs about others, and so on. The complexity becomes prohibitive when large number of agents are present and when decisions have to be made under time pressure. In this paper we investigate strategies intended to tame the computational burden by using off-line computation in conjunction with on-line reasoning. We investigate two approaches. First, we use rules compiled off-line to constrain alternative actions considered during on-line reasoning. This method minimizes overhead, but is not sensitive to changes in realtime demands of the situation at hand. Second, we use performance profiles computed off-line and the notion of urgency (i.e., the value of time) computed on-line to choose the amount of information to be included during on-line deliberation. This method can adjust to various levels of real-time demands, but incurs some overhead associated with iterative deepening. We test our framework with experiments in a simulated anti-air defense domain. The experiments show that both procedures are effective in reducing computation time while offering good performance under time pressure. | [
600,
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] | Train |
882 | 2 | Relevance Feedback and Query Expansion for Searching the Web: A Model for Searching a Digital Library : A fully operational large scale digital library is likely to be based on a distributed architecture and because of this it is likely that a number of independent search engines may be used to index different overlapping portions of the entire contents of the library. In any case, different media, text, audio, image, etc., will be indexed for retrieval by different search engines so techniques which provide a coherent and unified search over a suite of underlying independent search engines are thus likely to be an important part of navigating in a digital library. In this paper we present an architecture and a system for searching the world's largest DL, the world wide web. What makes our system novel is that we use a suite of underlying web search engines to do the bulk of the work while our system orchestrates them in a parallel fashion to provide a higher level of information retrieval functionality. Thus it is our meta search engine and not the underlying direct search engines th... | [
3099
] | Train |
883 | 0 | Generating and Using State Spaces of Object-Oriented Petri Nets : The article discusses the notion of state spaces of object-oriented Petri nets associated to the tool called PNtalk and the role of identifiers of dynamically appearing and disappearing instances within these state spaces. Methods of working with identifiers based on sophisticated naming rules and mechanisms for abstracting names are described and compared. Some optimizations of state space generating algorithms for the context of object-oriented Petri nets are briefly mentioned, as well. Key Words: Petri nets, object-orientation, state spaces, formal analysis and verification 1 Introduction Methods of formal analysis and verification has been developed as an alternative to simulation approaches of examining properties of complex systems. Although we are not always able to fully verify the behaviour of a system, even partial analysis or verification can reveal some errors which tend to be different from the ones found by simulation due to the different nature of formal analysis and... | [] | Validation |
884 | 1 | On Case-Based Representability and Learnability of Languages . Within the present paper we investigate case-based representability as well as case-based learnability of indexed families of uniformly recursive languages. Since we are mainly interested in case-based learning with respect to an arbitrary fixed similarity measure, case-based learnability of an indexed family requires its representability, first. We show that every indexed family is case-based representable by positive and negative cases. If only positive cases are allowed the class of representable families is comparatively small. Furthermore, we present results that provide some bounds concerning the necessary size of case bases. We study, in detail, how the choice of a case selection strategy influences the learning capabilities of a case-based learner. We define different case selection strategies and compare their learning power to one another. Furthermore, we elaborate the relations to Gold-style language learning from positive and both positive and negative examples. 1 Introdu... | [
1844,
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] | Train |
885 | 2 | Which Search Engine is best at finding Online Services? We report results for an independent, blind evaluation of the performance of 11 commercial search engines on 106 online service queries and on 54 topic relevance queries. We found a strong correlation between performance on the two types of query and significant differences between engines. | [
1849,
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] | Train |
886 | 3 | Analysis and Optimisation of Event-Condition-Action Rules on XML XML is a now a dominant standard for storing and exchanging information. With its increasing use in areas such as data warehousing and e-commerce, there is a rapidly growing need for rule-based technology to support reactive functionality on XML repositories. Eventcondition -action (ECA) rules automatically perform actions in response to events and are a natural facility to support such functionality. In this paper, we study ECA rules in the context of XML data. We define a simple language for specifying ECA rules on XML repositories. The language is illustrated by means of some examples, and its syntax and semantics are then specified more formally. We then investigate methods for analysing and optimising these ECA rules, a task which has added complexity in this XML setting compared with conventional active databases. 1 | [
1519,
1575,
1667,
1771,
2421
] | Validation |
887 | 2 | Maximum Likelihood Estimation for Filtering Thresholds Information filtering systems based on statistical retrieval models usually compute a numeric score indicating how well each document matches each profile. Documents with scores above profile-specific dissemination thresholds are delivered. An optimal dissemination threshold is one that maximizes a given utility function based on the distributions of the scores of relevant and non-relevant documents. The parameters of the distribution can be estimated using relevance information, but relevance information obtained while filtering is biased. This paper presents a new method of adjusting dissemination thresholds that explicitly models and compensates for this bias. The new algorithm, which is based on the Maximum Likelihood principle, jointly estimates the parameters of the density distributions for relevant and nonrelevant documents and the ratio of the relevant document in the corpus. Experiments with TREC-8 and TREC-9 Filtering Track data demonstrate the effectiveness of the algorithm. Keywords Information Filtering, Dissemination Threshold, Maximum Likelihood Estimation. 1. | [
435,
739,
1446,
2288
] | Train |
888 | 2 | Using Labeled and Unlabeled Data to Learn Drifting Concepts For many learning tasks, where data is collected over an extended period of time, one has to cope two problems. The distribution underlying the data is likely to change and only little labeled training data is available at each point in time. A typical example is information filtering, i. e. the adaptive classification of documents with respect to a particular user interest. Both the interest of the user and the document content change over time. A filtering system should be able to adapt to such concept changes. Since users often give little feedback, a filtering system should also be able to achieve a good performance, even if only few labeled training examples are provided. This paper proposes a method to recognize and handle concept changes with support vector machines and to use unlabeled data to reduce the need for labeled data. The method maintains windows on the training data, whose size is automatically adjusted so that the estimated generalization error is minimized. The approach is both theoretically well-founded as well as effective and efficient in practice. Since it does not require complicated parameterization, it is simpler to use and more robust than comparable heuristics. Experiments with simulated concept drift scenarios based on real-world text data compare the new method with other window management approaches and show that it can effectively select an appropriate window size in a robust way. In order to achieve an acceptable performance with fewer labeled training examples, the proposed method exploits unlabeled examples in a transductive way. 1 | [
1290,
1386,
1874,
2100,
2808,
2889
] | Train |
889 | 1 | Relating Chemical Structure to Activity: An Application of the Neural Folding Architecture : This paper is based on the neural folding architecture (FA). The FA is a recurrent neural network architecture which is especially suited for adaptive structure processing, i.e. learning approximations of mappings from symbolic term structures to IR n . The main objective of this paper is to demonstrate that the FA can be successfully applied to approximate quantitative structure activity relationships (QSARs), which play an important role during a drug design process. Several approaches for the conversion of a QSAR problem to suitable learning tasks for the FA are presented. Finally the FA is applied to a well-known QSAR benchmark, viz. the inhibition of E. coli dihydrofolate reductase by triazines. The achieved results are compared with results of other machine learning approaches on the same QSAR benchmark, and prove that the FA is significantly better. Keywords: recurrent neural networks, folding architecture, drug design, quantitative structure activity relationships, inhibit... | [
205
] | Test |
890 | 2 | Hierarchical Clustering for Datamining . This paper presents hierarchical probabilistic clustering methods for unsupervised and supervised learning in datamining applications. The probabilistic clustering is based on the previously suggested Generalizable Gaussian Mixture model. A soft version of the Generalizable Gaussian Mixture model is also discussed. The proposed hierarchical scheme is agglomerative and based on a L 2 distance metric. Unsupervised and supervised schemes are successfully tested on artificially data and for segmention of e-mails. 1 | [
878,
2468
] | Train |
891 | 3 | Complex Aggregation at Multiple Granularities . Datacube queries compute simple aggregates at multiple granularities. In this paper we examine the more general and useful problem of computing a complex subquery involving multiple dependent aggregates at multiple granularities. We call such queries "multi-feature cubes." An example is "Broken down by all combinations of month and customer, find the fraction of the total sales in 1996 of a particular item due to suppliers supplying within 10% of the minimum price (within the group), showing all subtotals across each dimension." We classify multi-feature cubes based on the extent to which fine granularity results can be used to compute coarse granularity results; this classification includes distributive, algebraic and holistic multi-feature cubes. We provide syntactic sufficient conditions to determine when a multi-feature cube is either distributive or algebraic. This distinction is important because, as we show, existing datacube evaluation algorithms can be used to compute multif... | [
1787,
3024
] | Train |
892 | 1 | Minimal Distance Neural Methods A general framework for minimal distance methods is presented. Radial Basis Functions (RBFs) and Multilayer Perceptrons (MLPs) neural networks are included in this framework as special cases. New versions of minimal distance methods are formulated. A few of them have been tested on a real-world datasets obtaining very encouraging results. | [
194
] | Test |
893 | 1 | Neuro-Mimetic Navigation Systems: A Computational Model of the Rat Hippocampus : We propose a bio-inspired approach to autonomous navigation based on some of the components that rats use for navigation. A spatial model of the environment is constructed by unsupervised Hebbian learning. The representation consists of a population of localized overlapping place elds, modeling place cell activity in the rat Hippocampus. Place elds are established by extracting spatio-temporal properties of the environment from visual sensory inputs. Visual ambiguities are resolved by means of path integration. Reinforcement learning is applied to use place cell activity for goal-oriented navigation. Experimental results obtained with a mobile Khepera robot are presented. Keywords: Autonomous robots, hippocampus, place elds, unsupervised learning, reinforcement learning, population vector coding, path integration. 1. Introduction The complexity of the autonomous navigation task is inherent in the concept of autonomy: Ideally, an autonomous agent should have a completely ... | [
2451
] | Train |
894 | 4 | Statistical Pattern Recognition Techniques for Multimodal Human Computer Interaction and Multimedia Information Processing This paper presents an extensive overview on statistical pattern recognition methods for a variety of different tasks, related to multimodal human-computer interaction and multimedia information processing. Typical tasks in the area of human-computer interaction include handwriting and gesture recognition, as well as pen-based retrieval of image databases. Multimedia information processing includes algorithms for document processing, video indexing or face recognition. The aim of the paper is to demonstrate to the speech community the usability of classical speech recognition algorithms, such as Hidden Markov Models and related statistical pattern recognition techniques, for a much larger variety of related problems in man-machine-communication and the ecient processing and retrieval of multimedia information. | [
1535
] | Validation |
895 | 1 | A Cellular System for Pattern Recognition using Associative Neural Networks : A cellular system for pattern recognition is presented in this paper. The cells are placed in a two dimensional array and they are capable of performing basic symbolic processing and exchanging messages about their state. Following a cellular automata like operation the aim of the system is to transform an initial symbolic description of a pattern to a correspondent object level representation. To this end, a hierarchical approach for the description of the structure of the patterns is followed. The underlying processing engine of the system is the AURA model of associative memory. The system is endowed with a learning mechanism utilizing the distributed nature of the architecture. A dedicated hardware platform is also available. 1 Introduction One of the basic characteristics of cellular automata [1] is their ability for parallel and distributed processing. This is due to the co-operation of relatively simple interconnected processing units called cells. These are connected followin... | [
1531
] | Train |
896 | 1 | A Data Mining Framework for Building Intrusion Detection Models There is often the need to update an installed Intrusion Detection System (IDS) due to new attack methods or upgraded computing environments. Since many current IDSs are constructed by manual encoding of expert knowledge, changes to IDSs are expensive and slow. In this paper, we describe a data mining framework for adaptively building Intrusion Detection (ID) models. The central idea is to utilize auditing programs to extract an extensive set of features that describe each network connection or host session, and apply data mining programs to learn rules that accurately capture the behavior of intrusions and normal activities. These rules can then be used for misuse detection and anomaly detection. New detection models are incorporated into an existing IDS through a meta-learning (or co-operative learning) process, which produces a meta detection model that combines evidence from multiple models. We discuss the strengths of our data mining programs, namely, classification, meta-learning... | [
1277,
2052,
2833
] | Test |
897 | 0 | TrIAs: Trainable Information Assistants for Cooperative Problem Solving Software agents are intended to perform certain tasks on behalf of their users. In many cases, however, the agent's competence is not sufficient to produce the desired outcome. This paper presents an approach to cooperative problem solving in which an information agent and its user try to support each other in the achievement of a particular goal. As a side effect the user can extend the agent's capabilities in a programming-by-demonstration dialog, thus enabling it to autonomously perform similar tasks in the future. 1 Introduction Software agents are intended to autonomously perform certain tasks on behalf of their users. In many cases, however, the agent's competence might not be sufficient to produce the desired outcome. Instead of simply giving up and leaving the whole task to the user, a much better alternative would be to precisely identify what the cause of the current problem is, communicate it to another agent who can be expected to be able (and willing) to help, and use th... | [
1154
] | Train |
898 | 1 | Markov Techniques for Object Localization With Force-Controlled Robots This paper deals with object localization with forcecontrolled robots in the Bayesian framework [1]. It describes a method based on Markov Localization techniques with a Monte Carlo implementation applied for solving 3D (6 degrees of freedom) global localization problems with force-controlled robots. The approach was successfully applied to problems such as the recursive localization of a box by a robot manipulator. | [
2734
] | Train |
899 | 3 | The Effect of Network Hierarchy Structure on Performance of ATM PNNI Hierarchical Routing Networks deploying hierarchical routing are recursively partitioned into sub-networks that do not reveal the full details of their internal structure outside their domains. Instead, an aggregated view of certain parameters that are associated with traversal within such sub-networks between their border nodes is advertised. The ATM PNNI standard and the Internet Nimrod architecture both adopt this approach for routing. This paper studies the effectiveness of ATM hierarchical routing protocols on networks with different hierarchical structures by simulation. Our study shows that, in general, the hierarchical source routing performs well compared to the global routing strategy which imposes no hierarchy, while utilizing less storage and communication overhead. For certain networks and topologies, the hierarchical routing performs better than the global routing. Different hierarchies imposed on the same topologies have significantly different performance on the throughput and routing dela... | [
1766
] | Test |
900 | 4 | PAD++: A Zoomable Graphical Sketchpad for Exploring Alternate Interface Physics We describe Pad++, a zoomable graphical sketchpad that we are exploring as an alternative to traditional window and icon-based interfaces. We discuss the motivation for Pad++, describe the implementation, and present prototype applications. In addition, we introduce an informational physics strategy for interface design and briefly contrast it with current design strategies. We envision a rich world of dynamic persistent informational entities that operate according to multiple physics specifically designed to provide cognitively facile access and serve as the basis for design of new computationally-based work materials. 1 To appear in the Journal of Visual Languages and Computing. Pad++: A Zoomable Graphical Sketchpad For Exploring Alternate Interface Physics 1 Benjamin B. Bederson James D. Hollan Computer Science Department University of New Mexico Albuquerque, NM 87131 (bederson@cs.unm.edu, hollan@cs.unm.edu) Ken Perlin Jonathan Meyer David Bacon Media Research Laboratory Co... | [
311,
2510
] | Train |
901 | 2 | Web Document Clustering: A Feasibility Demonstration Abstract Users of Web search engines are often forced to sift through the long ordered list of document “snippets” returned by the engines. The IR community has explored document clustering as an alternative method of organizing retrieval results, but clustering has yet to be deployed on the major search engines. The paper articulates the unique requirements of Web document clustering and reports on the first evaluation of clustering methods in this domain. A key requirement is that the methods create their clusters based on the short snippets returned by Web search engines. Surprisingly, we find that clusters based on snippets are almost as good as clusters created using the full text of Web documents. To satisfy the stringent requirements of the Web domain, we introduce an incremental, linear time (in the document collection size) algorithm called Suffix Tree Clustering (STC). which creates clusters based on phrases shared between documents. We show that STC is faster than standard clustering methods in this domain, and argue that Web document clustering via STC is both feasible and potentially beneficial. 1 | [
124,
193,
507,
721,
732,
1004,
1312,
1627,
2054,
2179,
2324,
2471,
2558,
3131
] | Train |
902 | 2 | TypTex: Inductive typological text classification by multivariate statistical analysis for NLP systems tuning/evaluation The increasing use of methods in natural language processing (NLP) which are based on huge corpora require that the lexical, morphosyntactic and syntactic homogeneity of texts be mastered. We have developed a methodology and associate tools for text calibration or "profiling" within the ELRA benchmark called "Contribution to the construction of contemporary french corpora" based on multivariate analysis of linguistic features. We have integrated these tools within a modular architecture based on a generic model allowing us on the one hand flexible annotation of the corpus with the output of NLP and statistical tools and on the other hand retracing the results of these tools through the annotation layers back to the primary textual data. This allows us to justify our interpretations. 1. Introduction Natural Language Processing (NLP) is increasingly dependent on corpus-based methods. The availability of corpora is no longer a problem, as huge and annotated corpora are now readily avail... | [
2484
] | Test |
903 | 5 | Execution Monitoring of High-Level Robot Programs. Imagine a robot that is executing a program on-line, and, insofar as it is reasonable to do so, it wishes to continue with this on-line program execution, no matter what exogenous events occur in the world. Execution monitoring is the robot's process of observing the world for discrepancies between the actual world and its internal representation of it, and recovering from such discrepancies. We provide a situation calculus-based account of such on-line program executions, with monitoring. This account relies on a specification for a single-step interpreter for the logic programming language Golog . The theory is supported by an implementation that is illustrated by a standard blocks world in which a robot is executing a Golog program to build a suitable tower. The monitor makes use of a simple kind of planner for recovering from malicious exogenous actions performed by another agent. After performing the sequence of actions generated by the recovery procedure, th... | [
219,
1722,
1961,
2144,
2940,
3127
] | Train |
904 | 2 | Discovering Informative Content Blocks from Web Documents In this paper, we propose a new approach to discover informative contents from a set of tabular documents (or Web pages) of a Web site. Our system, InfoDiscoverer, first partitions a page into several content blocks according to HTML tag <TABLE> in a Web page. Based on the occurrence of the features (terms) in the set of pages, it calculates entropy value of each feature. According to the entropy value of each feature in a content block, the entropy value of the block is defined. By analyzing the information measure, we propose a method to dynamically select the entropy-threshold that partitions blocks into either informative or redundant. Informative content blocks are distinguished parts of the page, whereas redundant content blocks are common parts. Based on the answer set generated from 13 manually tagged news Web sites with a total of 26,518 Web pages, experiments show that both recall and precision rates are greater than 0.956. That is, using the approach, informative blocks (news articles) of these sites can be automatically separated from semantically redundant contents such as advertisements, banners, navigation panels, news categories, etc. By adopting InfoDiscoverer as the preprocessor of information retrieval and extraction applications, the retrieval and extracting precision will be increased, and the indexing size and extracting complexity will also be reduced. | [
255,
1229,
1966,
2503
] | Train |
905 | 5 | The Computational Theory of Neural Networks In the present paper a detailed taxonomy of neural network models with various restrictions is presented with respect to their computational properties. The criteria of classification include e.g. feedforward and recurrent architectures, discrete and continuous time, binary and analog states, symmetric and asymmetric weights, finite size and infinite families of networks, deterministic and probabilistic models, etc. The underlying results concerning the computational power of perceptron, RBF, winner-take-all, and spiking neural networks are briey surveyed and completed by relevant references. | [
1783,
3070
] | Test |
906 | 2 | RoadRunner: Towards Automatic Data Extraction from Large Web Sites The paper investigates techniques for extracting data from HTML sites through the use of automatically generated wrappers. To automate the wrapper generation and the data extraction process, the paper develops a novel technique to compare HTML pages and generate a wrapper based on their similarities and differences. Experimental results on real-life data-intensive Web sites confirm the feasibility of the approach. 1 | [
985,
1294,
1393,
2068,
3053,
3098
] | Train |
907 | 3 | The Diagnosis Frontend of the dlv System This paper presents the Diagnosis Frontend of dlv, which is a knowledge representation system under development at the Technische Universität Wien. The kernel language of the system is an extension of disjunctive logic programming (DLP) by integrity constraints; it offers frontends to several advanced knowledge representation formalisms. The formal model of diagnosis employed in the frontend includes both abductive diagnosis (over DLP theories) and consistency-based diagnosis. For each of the two diagnosis modalities, generic diagnoses, single error diagnoses, and subset minimal diagnoses are considered. We illustrate the use of the frontend by showing the dlv encodings of several diagnosis problems. Thereafter, we discuss implementation issues. Diagnostic reasoning is implemented on the dlv engine through suitable translations of diagnostic problems into disjunctive logic programs, such that their stable models correspond to diagnoses. For the six kinds of diagnostic reasoning problems emerging from above, such reductions are provided | [
1449,
1919,
1939
] | Train |
908 | 3 | XML Query Languages: Experiences and Exemplars This paper identifies essential features of an XML query language by examining four existing query languages: XML-QL, YA T L , Lorel, and XQL. The first three languages come from the database community and possess striking similarities. The fourth comes from the document community and lacks some key functionality of the other three. | [
105,
2772
] | Train |
909 | 1 | Integrating Case Based Reasoning and Tabu Search for Solving Optimisation Problems Tabu search is an established heuristic optimisation technique for problems where exact algorithms are not available. It belongs to the same family as simulated annealing or genetic algorithms. It extends the basic iterative improvement scheme by adding control learning. A technique of this kind, intensification, captures experience established on a frequency-based analysis of past search. Experience is reused while the same optimisation process is going on in order to guide search to better solutions. In this paper, we introduce a case-based reasoning approach for control learning in tabu search. Search experience concerns operator selection and is represented by cases. The aim of case reuse is to improve conflict resolution. While the proposed method is domain independent, we present its application to the NPhard uncapacitated facility location problem. Experimental results show that adding our approach to a basic tabu search optimisation significantly improves solution quality on t... | [
1389,
2048
] | Test |
910 | 3 | Representing and Querying XML with Incomplete Information We study the representation and querying of XML with incomplete information. We consider a simple model for XML data and their DTDs, a very simple query language, and a representation system for incomplete information in the spirit of the representations systems developed by Imielinski and Lipski for relational databases. In the scenario we consider, the incomplete information about an XML document is continuously enriched by successive queries to the document. We show that our representation system can represent partial information about the source document acquired by successive queries, and that it can be used to intelligently answer new queries. We also consider the impact on complexity of enriching our representation system or query language with additional features. The results suggest that our approach achieves a practically appealing balance between expressiveness and tractability. The research presented here was motivated by the Xyleme project at INRIA, whose objectiveittodevelop a data warehouse for Web XML documents. 1. | [
1318
] | Validation |
911 | 0 | Information agents on the move: A survey on load-balancing with mobile agents Information agents process and integrate heterogeneous, distributed information. To achieve this task efficiently, some researchers promote the idea of mobile information agents [13, 53, 44, 20, 10], which migrate between a user's host and other hosts in the network. We outline the concepts behind mobile information agents and give a survey on load balancing, which aims to optimise distributed information processing. | [
50,
1035,
1943,
2553
] | Train |
912 | 1 | Feature Extraction and Learning Vector Quantization for Data Structures During the last years, folding architecture networks and the closely related concept of recursive neural networks have been developed for solving supervised learning tasks on data structures. In this paper we address the fundamental problem of finding fixedlength vector representations for structures in an unsupervised way. A solution based on ideas from feature extraction and folding architecture networks is proposed. Furthermore, a new method for supervised learning for data structures which combines ideas from learning vector quantization and folding architecture networks is suggested. 1 Introduction In almost all fields of scientific and technical reasoning, people and systems assisting them have to deal with structured objects . Examples are chemical structures, algebraic (mathematical) expressions and formulas, software source code, and conceptual and taxonomic graphs. With structured objects we mean objects which are composed of `smaller' objects, which may be structured too. T... | [
205
] | Test |
913 | 5 | Patterns in Property Specifications for Finite-State Verification Model checkers and other finite-state verification tools allow developers to detect certain kinds of errors automatically. Nevertheless, the transition of this technology from research to practice has been slow. While there are a number of potential causes for reluctance to adopt such formal methods, we believe that a primary cause is that practitioners are unfamiliar with specification processes, notations, and strategies. In a recent paper, we proposed a pattern-based approach to the presentation, codification and reuse of property specifications for finite-state verification. Since then, we have carried out a survey of available specifications, collecting over 500 examples of property specifications. We found that most are instances of our proposed patterns. Furthermore, we have updated our pattern system to accommodate new patterns and variations of existing patterns encountered in this survey. This paper reports the results of the survey and the current status of our pattern syste... | [
595
] | Train |
914 | 0 | Creatures: Artificial Life Autonomous Software Agents for Home Entertainment This paper gives a technical description of Creatures, a commercial home-entertainment software package. Creatures provides a simulated... | [
177
] | Train |
915 | 0 | Formal ReSpecT Logic tuple centres have s own that logic-ba d languages can be e#ectively exploited not only for building individual agents and enabling interagent communication in multi-agent ssG ms butals for ruli ng inter-agent communications as to builds cial behaviours In this paper, we formally define the notion of logic tuple centre as well as the operationals emantics of the logic-bas d language ReSpecT for the behaviours pecification of logic tuple centres . For this purpos e, we exploit a generals emantic framework for as ynchronous dis tributeds ys tems allowing a coordination medium to be formally denoted in as eparate and independent way with res pect to the whole coordinateds ys tem. This s hows that a logic-bas ed coordination medium does not limit agents and coordination languages to be logic-bas ed, but may ins tead enable agents of di#erents orts and technologies to be combined and coordinated in an e#ective way by exploiting a logic-bas ed approach. 1 Coordinationm edia form ulti... | [
102,
275,
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] | Train |
916 | 5 | From theory to practice: The UTEP robot in the AAAI 96 and AAAI 97 robot contests In this paper we describe the control aspects of Diablo, the UTEP mobile robot participant in two AAAI robot competitions. In the first competition, event one of the AAAI 96 robot contest, Diablo consistently scored 285 1 out of a total of 295 points. In the second competition, our robot won the first place in the event "Tidy Up" of the home vacuum contest. The main goal in this paper will be to show how the agent theories - based on action theories -- developed at UTEP and by Saffiotti et al. was used in the building of Diablo. 1 Introduction We participated 2 in the AAAI 96 robot navigation contest [KNH97] and the AAAI 97 home vacuum contest. In the first competition, our team scored 285 points in all runs of the contest out of a total of 295 points and was placed third in the finals. In the second competition, we won the first place in the event "Tidy Up." In this paper we relate theory of agents, particularly the one developed at UTEP, for higher level control, and the one by... | [
1192
] | Train |
917 | 5 | Efficient Atomic Cluster Optimization Using A Hybrid Extended Compact Genetic Algorithm With Seeded Population A recent study (Sastry & Xiao, 2001) proposed a highly reliable cluster optimization algorithm | [
1644
] | Train |
918 | 5 | Second Order Sufficient Conditions for Optimal Control Problems with Free Final Time: The Riccati Approach . Second order sufficient conditions (SSC) for control problems with control--state constraints and free final time are presented. Instead of deriving such SSC de initio, the control problem with free final time is tranformed into an augmented control problem with fixed final time for which well-known SSC exist. SSC are then expressed as a condition on the positive definiteness of the second variation. A convenient numerical tool for verifying this condition is based on the Riccati approach where one has to find a bounded solution of an associated Riccati equation satisfying specific boundary conditions. The augmented Riccati equations for the augmented control problem are derived and their modifications on the boundary of the control--state constraint are discussed. Two numerical examples, (1) the classical Earth-Mars orbit transfer in minimal time, (2) the Rayleigh problem in electrical engineering, demonstrate that the Riccati equation approach provides a viable numerical test of SS... | [] | Validation |
919 | 1 | A Synthetic Agent System for Bayesian Modeling Human Interactions When building statistical machine learning models from real data one of the most frequently encountered difficulties is the limited amount of training data compared to what is needed by the specific learning architecture. In order to deal with this problem we have developed a synthetic (simulated) agent training system that let us develop flexible prior models for recognizing human interactions in a pedestrian visual surveillance task. We demonstrate the ability to use these prior models to accurately classify real human behaviors and interactions with no additional tuning or training. 1 Introduction Agent-based solutions have been developed for many different application domains, and field-tested agent systems are steadily increasing in number. Agents are currently being applied in domains as diverse as computer games and interactive cinema, information retrieval and filtering, user interface design, electronic commerce, and industrial process control. In this paper we propose a nove... | [
51,
690,
2107
] | Validation |
920 | 1 | Rule Discovery with a Parallel Genetic Algorithm An important issue in data mining is scalability with respect to the size of the dataset being mined. In the paper we address this issue by presenting a parallel GA for rule discovery. This algorithm exploits both data parallelism, by distributing the data being mined across all available processors, and control parallelism, by distributing the population of individuals across all available processors. 1 | [] | Train |
921 | 1 | Data Mining in Soft Computing Framework: A Survey The present article provides a survey of the available literature on data mining using soft computing. A categorization has been provided based on the di#erent soft computing tools and their hybridizations used, the data mining function implemented, and the preference criterion selected by the model. The utility of the di#erent soft computing methodologies is highlighted. Generally fuzzy sets are suitable for handling the issues related to understandability of patterns, incomplete/noisy data, mixed media information and human interaction, and can provide approximate solutions faster. Neural networks are non-parametric, robust, and exhibit good learning and generalization capabilities in data-rich environments. Genetic algorithms provide e#cient search algorithms to select a model, from mixed media data, based on some preference criterion/objective function. Rough sets are suitable for handling di#erent types of uncertainty in data. Some challenges to data mining and the application of soft computing methodologies are indicated. An extensive bibliography is also included. Keywords--- Knowledge discovery, rule extraction, fuzzy logic, neural networks, genetic algorithms, rough sets, neuro-fuzzy computing I. | [
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922 | 1 | Mining Optimized Support Rules for Numeric Attributes Mining association rules on large data sets has received considerable attention in recent years. Association rules are useful for determining correlations between attributes of a relation and have applications in marketing, financial and retail sectors. Furthermore, optimized association rules are an effective way to focus on the most interesting characteristics involving certain attributes. Optimized association rules are permitted to contain uninstantiated attributes and the problem is to determine instantiations such that either the support, confidence or gain of the rule is maximized. In this paper, we generalize the optimized support association rule problem by permitting rules to contain disjunctions over uninstantiated numeric attributes. Our generalized association rules enable us to extract more useful information about seasonal and local patterns involving the uninstantiated attribute. For rules containing a single numeric attribute, we present a dynamic programming algorith... | [
3043
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923 | 3 | WSQ/DSQ: A Practical Approach for Combined Querying of Databases and the Web www-db.stanford.edu We present WSQ/DSQ (pronounced “wisk-disk”), a new approach for combining the query facilities of traditional databases with existing search engines on the Web. WSQ, for Web-Supported (Database) Queries, leverages results from Web searches to enhance SQL queries over a relational database. DSQ, for Database-Supported (Web) Queries, uses information stored in the database to enhance and explain Web searches. This paper focuses primarily on WSQ, describing a simple, low-overhead way to support WSQ in a relational DBMS, and demonstrating the utility of WSQ with a number of interesting queries and results. The queries supported by WSQ are enabled by two virtual tables, whose tuples represent Web search results generated dynamically during query execution. WSQ query execution may involve many high-latency calls to one or more search engines, during which the query processor is idle. We present a lightweight technique called asynchronous iteration that can be integrated easily into a standard sequential query processor to enable concurrency between query processing and multiple Web search requests. Asynchronous iteration has broader applications than WSQ alone, and it opens up many interesting query optimization issues. We have developed a prototype implementation of WSQ by extending a DBMS with virtual tables and asynchronous iteration; performance results are reported. 1 | [
475,
687,
2139,
2149,
2436,
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924 | 4 | Adaptive and Intelligent Technologies for Web-based Education The paper provides a review of adaptive and intelligent technologies in a context of Web-based distance education. We analyze what kind of technologies are available right now, how easy they can be implemented on the Web, and what is the place of these technologies in large-scale Web-based education. | [
666
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925 | 3 | Versus: A Temporal Web Repository Web data warehouses are useful for applications that need to process large amounts of Web data in a short time. This paper presents Versus, a Web repository model supporting object versioning and distributed operation for this kind of applications. Versioning allows applications to save the time dimension of data, enabling the development of new Web applications. Distribution allows parallel operation over massive amounts of data. We also present a prototype implementation of Versus along with results collected from the analisys of the execution of a distributed Web crawler simulator implemented as a Versus application. 1 | [
1170
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926 | 1 | Evolving Swimming Controllers for a Simulated Lamprey With Inspiration From Neurobiology This paper presents how neural swimming controllers for a simulated lamprey can be developed using evolutionary algorithms. A Genetic Algorithm is used for evolving the architecture of a connectionist model which determines the muscular activity of a simulated body. This work is inspired by the biological model developed by Ekeberg which reproduces the Central Pattern Generator observed in the real lamprey [Ekeberg 93]. In evolving artificial controllers, we demonstrate that a Genetic Algorithm can be an interesting design technique for neural controllers and that there exist alternative solutions to the biological connectivity. A variety of neural controllers are evolved which can produce the pattern of oscillations necessary for swimming. These patterns can be modulated through the external excitation applied to the network in order to vary the speed and the direction of swimming. The best evolved controllers cover larger ranges of frequencies, phase lags and speeds of swimming than ... | [
1132,
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927 | 0 | Using Declarative Constraints to Specify the Data Model of Multi-User Application Complex applications such as multi-user applications may fruitfully be viewed as being composed of a number of independent agents which access and modify a shared data structure. We will view this shared data so as to include the domain data being viewed and edited as well as the entire user interface state. | [
140
] | Validation |
928 | 4 | Estimating the Orientation and Recovery of Text Planes in a Single Image A method for the fronto-parallel recovery of paragraphs of text under full perspective transformation is presented. The horizontal vanishing point of the text plane is found using an extension of 2D projection profiles. This allows the accurate segmentation of the lines of text. Analysis of the lines will then reveal the style of justification of the paragraph, and provide an estimate of the vertical vanishing point of the plane. The text is finally recovered to a fronto-parallel view suitable for OCR or other higher-level recognition. | [
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] | Train |
929 | 4 | Human factors in ATC alarms and notifications design: an experimental evaluation With the growing use of computerised working position, alarm design on air traffic control displays is a concern as events to be notified increase in number and diversity. Safety requires visual notifications that can be efficiently detected and understood. It also requires that no information on the radar display is obscured by the visual notifications. We also need to design hierarchies of notifications, from most severe to benign. Taking advantage of the current graphical capabilities of computers, we have identified and explored various dimensions in visual alarm design. We present in this paper an experimental evaluation, in terms of detection time and precision, of several of those dimensions: opacity, size, temporal profile of animation and signal frequency. From our results, we conclude that opacity, size and temporal profile of animation are well suited to introduce some nuances in the way we convey notifications on visual displays. We also show that detection of a given signa... | [
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] | Train |
930 | 3 | Integrating Keyword Search into XML Query Processing Due to the popularity of the XML data format, several query languages for XML have been proposed, specially devised to handle data whose structure is unknown, loose, or absent. While these languages are rich enough to allow for querying the content and structure of an XML document, a varying or unknown structure can make formulating queries a very difficult task. We propose an extension to XML query languages that enables keyword search at the granularity of XML elements, that helps novice users formulate queries, and also yields new optimization opportunities for the query processor. We present an implementation of this extension on top of a commercial RDBMS; we then discuss implementation choices and performance results. Keywords XML query processing, full-text index 1 Introduction There is no doubt that XML is rapidly becoming one of the most important data formats. It is already used for scientific data (e.g., DNA sequences), in linguistics (e.g., the Treebank database at the U... | [
475,
1086,
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] | Train |
931 | 2 | Methods for Sampling Pages Uniformly from the World Wide Web We present two new algorithms for generating uniformly random samples of pages from the World Wide Web, building upon recent work by Henzinger et al. (Henzinger et al. 2000) and Bar-Yossef et al. (Bar-Yossef et al. 2000). Both algorithms are based on a weighted random-walk methodology. The first algorithm (DIRECTED-SAMPLE) operates on arbitrary directed graphs, and so is naturally applicable to the web. We show that, in the limit, this algorithm generates samples that are uniformly random. The second algorithm (UNDIRECTED-SAMPLE) operates on undirected graphs, thus requiring a mechanism for obtaining inbound links to web pages (e.g., access to a search engine). With this additional knowledge of inbound links, the algorithm can arrive at a uniform distribution faster than DIRECTEDSAMPLE, and we derive explicit bounds on the time to convergence. In addition, we evaluate the two algorithms on simulated web data, showing that both yield reliably uniform samples of pages. We also compare our results with those of previous algorithms, and discuss the theoretical relationships among the various proposed methods. | [
488,
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] | Test |
932 | 1 | Gradient-Based Learning Applied to Document Recognition Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradientbased learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters, with minimal preprocessing. This paper reviews various methods applied to handwritten character recognition and compares them on a standard handwritten digit recognition task. Convolutional neural networks, which are specifically designed to deal with the variability of two dimensional (2-D) shapes, are shown to outperform all other techniques. Real-life document recognition systems are composed of multiple modules including field extraction, segmentation, recognition, and language modeling. A new learning paradigm, called graph transformer networks (GTN’s), allows such multimodule systems to be trained globally using gradient-based methods so as to minimize an overall performance measure. Two systems for online handwriting recognition are described. Experiments demonstrate the advantage of global training, and the flexibility of graph transformer networks. A graph transformer network for reading a bank check is also described. It uses convolutional neural network character recognizers combined with global training techniques to provide record accuracy on business and personal checks. It is deployed commercially and reads several million checks per day. | [
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] | Validation |
933 | 0 | On the Emergence of Macro Spatial Structures in Dissipative Cellular Automata, and its Implications for Agent-based Distributed Computing This paper describes the peculiar behavior observed in a class of cellular automata that we have defined as "dissipative", i.e., cellular automata that are "open" and makes it possible for the environment to influence the evolution of the automata. Peculiar in the dynamic evolution of this class of cellular automata is that stable macro-level spatial structures emerge from local interactions among cells, a behavior that does not emerge when the cellular automaton is "closed", i.e., when the state of a cell is not influenced by the external world. On this basis, the paper discusses the relations of the performed experiments with the area of open distributed computing, and in particular of agent-based distributed computing. The basic intuition is that dissipative cellular automata express characteristics that strongly resembles those of wide-area open distributed systems based on autonomous and situated active components -- as agents are. Accordingly, similar sorts of macrolevel behaviors are likely to emerge and need to be studied, controlled, and possibly fruitfully exploited. | [
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] | Train |
934 | 1 | Robust Classification Systems for Imprecise Environments In real-world environments it is usually difficult to specify target operating conditions precisely. This uncertainty makes building robust classification systems problematic. We show that it is possible to build a hybrid classifier that will perform at least as well as the best available classifier for any target conditions. This robust performance extends across a wide variety of comparison frameworks, including the optimization of metrics such as accuracy, expected cost, lift, precision, recall, and workforce utilization. In some cases, the performance of the hybrid can actually surpass that of the best known classifier. The hybrid is also efficient to build, to store, and to update. Finally, we provide empirical evidence that a robust hybrid classifier is needed for many real-world problems. Introduction Traditionally, classification systems have been built by experimenting with many different classifiers, comparing their performance and choosing the classifier that performs best.... | [
688,
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] | Train |
935 | 2 | Intelligent Retrieval Of Digital Images From Large Geospatial Databases In this paper we present the development of a spatial data management system utilizing sketch-based queries for the content-based retrieval of digital images from topographic databases. We discuss our overall strategy and associated algorithmic and implementational aspects, and present the associated database design issues. The query tools devised in this research are employing user-provided sketches of the shape and spatial configuration of the object(s) which should appear in the images to be retrieved. Our strategy is scaleindependent. It is inspired by least-squares matching (lsm), and represents an extension of lsm to function with a variety of raster representations. The results are ranked according to statistical scores and the user can subsequently narrow or broaden his/her search according to the previously obtained results and the purpose of the search. 1 INTRODUCTION Intelligent image retrieval from large databases is one of the novel applications which are receiving increa... | [
207
] | Validation |
936 | 3 | Containment of Conjunctive Regular Path Queries with Inverse Reasoning on queries is a basic problem both in knowledge representation and databases. A fundamental form of reasoning on queries is checking containment, i.e., verifying whether one query yields necessarily a subset of the result of another query. Query containment is crucial in several contexts, such as query optimization, knowledge base verification, information integration, database integrity checking, and cooperative answering. In this paper we address the problem of query containment in the context of semistructured knowledge bases, where the basic querying mechanism, namely regular path queries, asks for all pairs of objects that are connected by a path conforming to a regular expression. We consider conjunctive regular path queries with inverse, which extend regular path queries with the possibility of using both the inverse of binary relations, and conjunctions of atoms, where each atom specifies that one regular path query with inverse holds between two v... | [
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937 | 3 | Flexible Distributed Database Management with AgentTeam . Ideally, distributed management of relational data should enable the sharing of consistent data and provide system transparency. In contrast to information retrieval, users can access compact data and utilise it for further relational processing. However, distributed database management is still a challenging research area that involves bridging syntactic and semantic heterogeneity of data as well as of functionality. Since, existing distributed database management systems were usually built with a focus on the implementation of some dedicated protocols for distributed database management, they are inflexible for major modifications or exchange of the protocols. In addition, their software architecture usually does not comply with well-known design paradigms, which could facilitate the maintenance of the software system. We present an agent-based approach for flexible distributed database management, where independent distributed database management protocols and methods are... | [
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] | Train |
938 | 3 | Modeling Temporal Consistency in Data Warehouses Real-world changes are generally discovered delayed by computer systems. The typical update patterns for traditional data warehouses on an overnight or even weekly basis enlarge this propagation delay until the information is available to knowledge workers. The main contribution of the paper is the identification of two different temporal characterizations of the information appearing in a data warehouse: one is the classical description of the time instant when a given fact occurred, the other represents the instant when the information has been entered into the system. We present an approach for modeling conceptual time consistency problems and introduce a data model that deals with timely delays and supports knowledge workers to determine what the situation was in the past, knowing only the information available at a given instant of time. 1 | [
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939 | 4 | Layout Rules for Graphical Web Documents The number of companies, institutions, and individuals competing for attention in the World-Wide Web is growing exponentially. This makes designing informative, easy-to-grasp, and visually appealing documents not only important for userfriendly information presentation, but also the key to success for any information provider. In this paper, we present layout guidelines for textual and graphical, static and dynamic, 2-D and 3-D Web documents which are drawn from fields as diverse as typography, Gestalt psychology, architecture, hypertext authoring, and human-computer interaction. Web documents are classified into five basic types, and our layout rules are applied to each of these. Finally, we show how currently evolving standards (HTML 3.0 for text and still graphics, Java for 2-D animation, and VRML for 3-D worlds) support applying those rules. 1 Introduction Whenever a new information-conveying technology is invented, it usually takes many years until authors develop new media that ... | [
828
] | Validation |
940 | 0 | Implementing Incremental Code Migration with XML We demonstrate how XML and related technologies can be used for code mobility at any granularity, thus overcoming the restrictions of existing approaches. By not fixing a particular granularity for mobile code, we enable complete programs as well as individual lines of code to be sent across the network. We define the concept of incremental code mobility as the ability to migrate and add, remove, or replace code fragments (i.e., increments) in a remote program. The combination of fine-grained and incremental migration achieves a previously unavailable degree of flexibility. We examine the application of incremental and fine-grained code migration to a variety of domains, including user interface management, application management on mobile thin clients, for example PDAs, and management of distributed documents. Keywords Incremental Code Migration, XML Technologies 1 INTRODUCTION The increasing popularity of Java and the spread of Webbased technologies are contributing to a growing ... | [
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] | Train |
941 | 5 | Foundations for Bayesian networks Bayesian networks are normally given one of two types of foundations: they are either treated purely formally as an abstract way of representing probability functions, or they are interpreted, with some causal interpretation given to the graph in a network and some standard interpretation of probability given to the probabilities specified in the network. In this chapter I argue that current foundations are problematic, and put forward new foundations which involve aspects of both the interpreted and the formal approaches. One standard approach is to interpret a Bayesian network objectively: the graph in a Bayesian network represents causality in the world and the specified probabilities are objective, empirical probabilities. Such an interpretation founders when the Bayesian network independence assumption (often called the causal Markov condition) fails to hold. In §2 I catalogue the occasions when the independence assumption fails, and show that such failures are pervasive. Next, in §3, I show that even where the independence assumption does hold objectively, an agent’s causal knowledge is unlikely to satisfy the assumption with respect to her subjective probabilities, and that slight differences between an agent’s subjective Bayesian network and an objective Bayesian network can lead to large differences between probability distributions determined by these networks. To overcome these difficulties I put forward logical Bayesian foundations in §5. I show that if the graph and probability specification in a Bayesian network are thought of as an agent’s background knowledge, then the agent is most rational if she adopts the probability distribution determined by the | [
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942 | 0 | How to Avoid Knowing It All Beliefs have been formally modelled in the last decades using doxastic logics. The possible worlds model and its associated Kripke semantics provide an intuitive semantics for these logics, but they seem to commit us to model agents that are logically omniscient (they believe every classical tautology) and perfect reasoners (their beliefs are closed under classical deductive closure). Thus, this model would not be appropriate to model non-ideal agents, that have resource limitations that prevent them from attaining such levels of doxastic competence. This report contains a statement of these problems and a brief survey of some of the most interesting approaches that have been suggested to overcome them. Contents 1 Formal models of belief 3 1.1 Possible worlds and Kripke semantics . . . . . . . . . . . . . . . . . . . . . 3 1.2 Logical omniscience and perfect reasoning . . . . . . . . . . . . . . . . . . 5 2 Avoiding logical omniscience 7 2.1 Syntactic approaches . . . . . . . ... | [
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] | Train |
943 | 2 | Data Mining Models as Services on the Internet The goal of this article is to raise a debate on the usefulness of providing data mining models as services on the internet. These services can be provided by anyone with adequate data and expertise and made available on the internet for anyone to use. For instance, Yahoo or Altavista, given their huge categorized document collection, can train a document classifier and provide the model as a service on the internet. This way data mining can be made accessible to a wider audience instead of being limited to people with the data and the expertise. A host of practical problems need to be solved before this idea can be made to work. We identify them and close with an invitation for further debate and investigation. 1. | [
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] | Validation |
944 | 2 | Browsing Information Spaces This document contains the generic background and targets of the Advanced Information Space Browser, which is planned to be included in the Decomate-II library information system at Tilburg University. It gives an overview of the current state-of-the-art in information retrieval, focusing especially on topic browsers, thesauri, and semantic networks. Some preliminary ideas for actual implementations are included as well. Keywords: Semantic network, conceptual modeling, topic browsing, document retrieval, Decomate-II. 1 Introduction The Decomate-II Library System, currently under development at Tilburg University in cooperation with several European partners, aims at a Web-based single point user interface to a multitude of (possibly distributed) databases. A single user query, usually a set of keywords, is mapped to all connected databases, each with its own query language, data schema, and contents. The individual query results are merged together by the system, post-processed to eli... | [] | Train |
945 | 3 | Management and Query Processing of one dimensional Intervals with the UB-Tree The management and query processing of one dimensional intervals is a special case of extended object handling. One dimensional intervals play an important role in temporal databases and they can also be used for fuzzy matching, fuzzy logic and measuring quality classes, etc. Most existing multidimensional access methods for extended objects do not address this special problem and most of them are main memory access methods that do not support e#cient access to secondary storage. The research in the application of the UB-Tree to extended objects is part of my doctoral work. The contribution of this article is a specific solution for managing and querying one dimensional intervals with the UB-Tree, a multidimensional extension of the classical B-Tree. The combination of UB-Tree and transformation of extended objects to parameter space is an e#ective solution for this specific problem. Keywords: one dimensional intervals, extended object handling, point query, range query, spatial data... | [
992
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946 | 3 | Privacy Preserving Distributed Data Mining em, there is a simple distributed solution that provides a degree of privacy to the individual sites. An example association rule could be: Received F lu shot and age > 50 implies hospital admission, where at least 5% of insured meet all the criteria (support), and at least 30% of those meeting the flu shot and age criteria actually require hospitalization (confidence). There are algorithms to e#ciently find all association rules with a minimum level of support. We can easily extend this to the distributed case using the following lemma: If a rule has support > k% valid The Data Approach Figure 1: Data Warehouse approach to Distributed Data Mining globally, it must have support > k% on at least one of the individual sites. A distributed algorithm for this would work as follows: Request that each site send all rules with support at least k. For e | [
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] | Train |
947 | 3 | Defining Views In An Image Database System : A view mechanism can help handle the complex semantics in emerging application areas such as image databases. This paper presents the view mechanism we defined for the DISIMA image database system. Since DISIMA is being developed on top of an object-oriented database system, we first propose apowerful object-oriented view mechanism based on the separation between types (interface functions) and classes that manage objects of the same type. The image view mechanism uses our object-oriented view mechanism to allow us to give differentsemantics to the same image. The solution is based on the distinction between physical salient objects which are interesting objects in an image and logical salient objects which are the meanings of these objects. 14.1 INTRODUCTION Views have been widely used in relational database management systems to extend modeling capabilities and to provide data independence. Basically, views in a relational database can be seen as formulae defining virtua... | [
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948 | 3 | On the Expressive Power of Data Integration Systems There are basically two approaches for designing a data integration system. In the global-as-view (GAV) approach, one maps the concepts in the global schema to views over the sources, whereas in the local-as-view (LAV) approach, one maps the sources into views over the global schema. The goal of this paper is to relate the two approaches with respect to their expressive power. | [
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] | Train |
949 | 2 | The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity We describe a joint probabilistic model for modeling the contents and inter-connectivity of document collections such as sets of web pages or research paper archives. The model is based on a probabilistic factor decomposition and allows identifying principal topics of the collection as well as authoritative documents within those topics. Furthermore, the relationships between topics is mapped out in order to build a predictive model of link content. Among the many applications of this approach are information retrieval and search, topic identification, query disambiguation, focused web crawling, web authoring, and bibliometric analysis. | [
471,
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538,
1718,
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950 | 2 | MIND: An architecture for multimedia information retrieval in federated digital libraries Introduction Today, people have routine access to a huge number of heterogeneous and distributed digital libraries. To satisfy an information need, relevant libraries have to be selected, the information need has to be reformulated for every library w. r. t. its schema and query syntax, and the results have to be fused. This is an ineffective manual task for which accurate tools are desirable. MIND (which we are currently developing in an EU project) is an end-to-end solution for federated digital libraries which covers all these issues. We start from information retrieval approaches which focus on retrieval quality, but mostly only consider monomedial and homogeneous sources. We will extend these approaches for dealing with different kinds of media (text, facts, images and transcripts of speech recognition) as well as handling heterogeneous libraries (e.g., with different schemas). Another innovation is that MIND also considers non-co-operating libraries which only provide the | [
521,
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] | Validation |
951 | 1 | Multi-Robot Target Acquisition using Multiple Objective Behavior Coordination In this paper we propose an approach to multi-robot coordination in the context of cooperative target acquisition. The approach is based on multiple objective behavior coordination extended to multiple robots. It provides mechanisms for distributed command fusion across a group of robots to pursue multiple goals of multiple robots in parallel. The mechanisms enable each robot to select actions that not only benefit itself but also benefit the group as a whole. Experimental results with two mobile robots validate that, by using this method, a group of robots can successfully track and acquire a moving target. 1 Introduction Cooperation of a team of robots in unknown settings poses complex control problems which require solutions that guarantee a suitable trade-off between a multitude of (potentially) conflicting task objectives within and among the robots. For instance, an action that is optimal with respect to a particular robot might be unacceptable with respect to the others. Thus ... | [
963,
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] | Train |
952 | 0 | Dynamic Agent Discovery One of the issues that has gained importance in the real world applications of agent systems is the bootstrapping of agents. | [
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953 | 1 | Mixtures of Linear Subspaces for Face Detection We present two methods using mixtures of linear subspaces for face detection in gray level images. One method uses a mixture of factor analyzers to concurrently perform clustering and, within each cluster, perform local dimensionality reduction. The parameters of the mixture model are estimated using an EM algorithm. A face is detected if the probability of an input sample is above a predened threshold. The other mixture of subspaces method uses Kohonen 's self-organizing map for clustering and Fisher Linear Discriminant to nd an optimal projection and a Gaussian distribution to model the class-conditional density function of the projected samples for each class. The parameters of the class-conditional density functions are maximum likelihood estimates and the decision rule is also based on maximum likelihood. A wide range of face images including ones in dierent poses, with dierent expressions and under dierent lighting conditions are used as the training set to capture the varia... | [
1554,
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] | Validation |
954 | 4 | Broadcasting Consistent Data to Mobile Clients with Local Cache Although data broadcast has been shown to be an efficient method for disseminating data items in a mobile computing system with large number of clients, the issue on how to ensure currency and consistency of the data items has not been examined adequately. | [
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955 | 4 | Supporting Creativity with Advanced Information-Abundant User Interfaces A challenge for human-computer interaction researchers and user interface designers is to construct information technologies that support creativity. This ambitious goal can be attained if designers build on an adequate understanding of creative processes. This paper describes a model of creativity, the four-phase genex framework for generating excellence: - Collect: learn from previous works stored in digital libraries, the web, etc. - Relate: consult with peers and mentors at early, middle and late stages - Create: explore, compose, discover, and evaluate possible solutions - Donate: disseminate the results and contribute to the digital libraries, the web, etc. Within this integrated framework, there are eight activities that require human-computer interaction research and advanced user interface design. This paper concentrates on techniques of information visualization that support creative work by enabling users to find relevant information resources, identify desired items in a se... | [
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956 | 3 | Curio: A Novel Solution for Efficient Storage and Indexing in Data Warehouses Efficient query processing is a critical requirement for data warehousing systems as decision support applications often require interactive response times to answer complex, ad-hoc queries (e.g., aggregations, multi-way joins) over vast repositories of data (e.g., hundreds of gigabytes to terabytes in size). The most common approach used to improve On-Line Analytical Processing (OLAP) query performance is to utilize indexes or access structures to quickly access the base data. A major drawback to this approach is that it often incurs significant overhead as the access structures must be stored in addition to the base data. In this paper, we present Curio, a data repository and OLAP query server, which provides drastically improved performance for ad-hoc queries, while simultaneously reducing the storage costs associated with warehousing. Curio, a data storage and access technology for data warehouses recently developed by Muninn Technologies, LLC, is based on a novel paradigm that all... | [
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957 | 4 | More Than Just a Pretty Face: Affordances of Embodiment Prior research into embodied interface agents has found that users like them and find them engaging. In this paper, we argue that embodiment can serve an even stronger function if system designers use actual human conversational protocols in the design of the interface. Communicative behaviors such as salutations and farewells, conversational turn-taking with interruptions, and referring to objects using pointing gestures are examples of protocols that all native speakers of a language already know how to perform and that can thus be leveraged in an intelligent interface. We discuss how these protocols are integrated into Rea, an embodied, multi-modal conversational interface agent who acts as a real-estate salesperson, and we show why embodiment is required for their successful implementation. INTRODUCTION There is a qualitative difference between face-to-face conversation and other forms of human-human communication [4]. Businesspeople and academics routinely travel long distances ... | [
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] | Train |
958 | 1 | Optimizing Neural Networks for Time Series Prediction In this paper we investigate the effective design of an appropriate neural network model for time series prediction based on an evolutionary approach. In particular, the Breeder Genetic Algorithms are considered to face contemporaneously the optimization of (i) the design of a neural network architecture and (ii) the choice of the best learning method. The effectiveness of the approach proposed is evaluated on a standard benchmark for prediction models, the Mackey--Glass series. 1. Introduction The main motivation for time series research is to provide a prediction when a mathematical model of a phenomenon is either unknown or incomplete. A time series consists of measurements or observations of the previous outcomes of a phenomenon that are made sequentially over time. If these consecutive observations are dependent on each other then it is possible to attempt a prediction. Clearly it is supposed that the process is somehow predictable. The time series prediction problems are usually... | [
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959 | 3 | Increasing the Expressiveness of Analytical Performance Models for Replicated Databases . The vast number of design options in replicated databases requires efficient analytical performance evaluations so that the considerable overhead of simulations or measurements can be focused on a few promising options. A review of existing analytical models in terms of their modeling assumptions, replication schemata considered, and network properties captured, shows that data replication and intersite communication as well as workload patterns should be modeled more accurately. Based on this analysis, we define a new modeling approach named 2RC (2-dimensional replication model with integrated communication). We derive a complete analytical queueing model for 2RC and demonstrate that it is of higher expressiveness than existing models. 2RC also yields a novel bottleneck analysis and permits to evaluate the trade-off between throughput and availability. 1 Introduction Replication management in distributed databases concerns the decision when and where to allocate physical copies of ... | [
2512,
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960 | 3 | Privacy Preserving Association Rule Mining in Vertically Partitioned Data Privacy considerations often constrain data mining projects. This paper addresses the problem of association rule mining where transactions are distributed across sources. Each site holds some attributes of each transaction, and the sites wish to collaborate to identify globally valid association rules. However, the sites must not reveal individual transaction data. We present a two-party algorithm for efficiently discovering frequent itemsets with minimum support levels, without either site revealing individual transaction values. | [
995,
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] | Train |
961 | 1 | Autonomous Helicopter Control using Reinforcement Learning Policy Search Methods Many control problems in the robotics field can be cast as Partially Observed Markovian Decision Problems (POMDPs), an optimal control formalism. Finding optimal solutions to such problems in general, however is known to be intractable. It has often been observed that in practice, simple structured controllers suffice for good sub-optimal control, and recent research in the artificial intelligence community has focused on policy search methods as techniques for finding sub-optimal controllers when such structured controllers do exist. Traditional model-based reinforcement learning algorithms make a certainty equivalence assumption on their learned models and calculate optimal policies for a maximumlikelihood Markovian model. In this work, we consider algorithms that evaluate and synthesize controllers under distributions of Markovian models. Previous work has demonstrated that algorithms that maximize mean reward with respect to model uncertainty leads to safer and more robust controll... | [
1765,
1788
] | Train |
962 | 5 | The CMUnited-97 Simulator Team . The Soccer Server system provides a rich and challenging multiagent, real-time domain. Agents must accurately perceive and act despite a quickly changing, largely hidden, noisy world. They must also act at several levels, ranging from individual skills to full-team collaborative and adversarial behaviors. This article presents the CMUnited-97 approaches to the above challenges which helped the team to the semifinals of the 29-team RoboCup-97 tournament. 1 Introduction The Soccer Server system [5] used at RoboCup-97 [2] provides a rich and challenging multiagent, real-time domain. Sensing and acting is noisy, while interagent communication is unreliable and low-bandwidth. In order to be successful, each agent in a team must be able to sense and act in real time: sensations arrive at unpredictable intervals while actions are possible every 100ms. Furthermore, since the agents get local, noisy sensory information, they must have a method of converting their sensory inputs into a good w... | [
287,
346,
864,
1246,
1573,
1630
] | Test |
963 | 1 | Ayllu: Distributed Port-Arbitrated Behavior-Based Control . Distributed control of a team of mobile robots presents a number of unique challenges, including highly unreliable communication, real world task and safety constraints, scalability, dynamic reconfigurability, heterogenous platforms, and a lack of standardized tools or techniques. Similar problems plagued development of single robots applications until the "behavior-based" revolution led to new techniques for robot control based on port-arbitrated behaviors (PAB). Though there are now many implementations of systems for behavior-based control of single robots, the potential for distributing such control across robots for multi-agent control has not until now been fully realized. This paper presents Ayllu, a system for distributed multi-robot behavioral control. Ayllu allows standard PAB interaction (message passing, inhibition, and suppression) to take place over IP networks, and extends the PAB paradigm to provide for arbitrary scalability. We give a brief overview of the Broadcast... | [
281,
528,
767,
951,
2134,
2828
] | Train |
964 | 1 | Evolving an Optimal De/Convolution Function for the Neural Net Modules of ATR's Artificial Brain Project This paper reports on efforts to evolve an optimum de/convo-lution function to be used to convert analog to binary signals (spike trains) and vice versa for the binary input/output signals of the neural net circuit modules evolved at electronic speeds by the so-called "CAM-Brain Machine (CBM)" of ATR's Artificial Brain Project [1, 2, 3]. The CBM is an FPGA based piece of hardware which will be used to evolve tens of thousands of cellular automata based neural network circuits or modules at electronic speeds in about a second each, which are then downloaded into humanly architected artificial brains in a large RAM space [2, 3]. Since state-of-the-art programmable FPGAs constrained us to use 1 bit binary signaling in our neural model (the "CoDi-1Bit" model [4]), an efficient de/convolution technique is needed to convert digital signals to analog and vice versa, so that "evolutionary engineers" (EEs) who evolve the many modules, can think it terms of analog signals when they need to, rath... | [
2767
] | Validation |
965 | 3 | Query Rewriting for Semistructured Data We address the problem of query rewriting for TSL, a language for querying semistructured data. We develop and present an algorithm that, given a semistructured query q and a set of semistructured views V, finds rewriting queries, i.e., queries that access the views and produce the same result as q. Our algorithm is based on appropriately generalizing containment mappings, the chase, and unification -- techniques that were developed for structured, relational data. We also develop an algorithm for equivalence checking of TSL queries. We show that the algorithm is sound and complete for TSL, i.e., it always finds every TSL rewriting query of q, and we discuss its complexity. We extend the rewriting algorithm to use available structural constraints (such as DTDs) to find more opportunities for query rewriting. We currently incorporate the algorithm in the TSIMMIS system. 1 Introduction Recently, many semistructured data models, query and view definition languages have been proposed [2... | [
679,
1061,
1667,
2080
] | Train |
966 | 1 | Inductive Learning and Case-Based Reasoning This paper describes an application of an inductive learning techniques to case-based reasoning. We introduce two main forms of induction, define case-based reasoning and present a combination of both. The evaluation of the proposed system, called TA3, is carried out on a classification task, namely character recognition. We show how inductive knowledge improves knowledge representation and in turn flexibility of the system, its performance (in terms of classification accuracy) and its scalability. 1. Introduction Inductive learning is a process of generalizing specific facts or observations [MCM86]. It is a basic strategy by which one can acquire knowledge. There are two main forms associated with inductive learning: 1. Instance-to-class induction, where the learning system is presented with independent instances, representing class and the task is to induce a general description of the class. 2. Clustering problem arises when several objects or situations are presented to a learner... | [
631,
1438,
2281,
2581,
2878
] | Train |
967 | 1 | Logical Case Memory Systems: Foundations And Learning Issues The focus of this paper is on the introduction of a quite general type of case-based reasoning systems called logical case memory systems. The development of the underlying concepts has been driven by investigations in certain problems of case-based learning. Therefore, the present development of the target concepts is accompanied by an in-depth discussion of related learning problems. Logical case memory systems provide some formal framework for the investigation and for the application of structural similarity concepts. Those concepts have some crucial advantage over traditional numerical similarity concepts: The result of determining a new case's similarity to some formerly experienced case can be directly taken as a basis for performing case adaptation. Essentially, every logical case memory system consists of two constituents, some partially ordered case base and some partially ordered set of predicates. Cases are terms, in a logical sense. Given some problem case, every predicat... | [
2171,
2395,
2890,
3160,
3176
] | Train |
968 | 4 | Cosmo: A Life-like Animated Pedagogical Agent with Deictic Believability Life-like animated interface agents for knowledgebased learning environments can provide timely, customized advice to support students' problem solving. Because of their strong visual presence, they hold significant promise for substantially increasing students' enjoyment of their learning experiences. A key problem posed by life-like agents that inhabit artificial worlds is deictic believability. In the same manner that humans refer to objects in their environment through judicious combinations of speech, locomotion, and gesture, animated agents should be able to move through their environment, and point to and refer to objects appropriately as they provide problemsolving advice. In this paper we describe a framework for achieving deictic believability in animated agents. A deictic behavior planner exploits a world model and the evolving explanation plan as it selects and coordinates locomotive, gestural, and speech behaviors. The resulting behaviors and utterances are believable, and... | [
2486,
2892
] | Train |
969 | 4 | Constructing A Realistic Head Animation Mesh for a Specific Person This paper addresses the problem of constructing an realistic and complete animation mesh that portrays a specific person's head geometry and texture. Our approach deforms a prototype mesh containing vector-based delineated muscles to fit one or more geometric models obtained from stereo image pairs of a specific person's head. The resulting personalized mesh facilitates animation with the same realism and predictability as the original prototype mesh. The model construction requires some manual interaction, however automatic refinement methods reduce the need for precision. The sensing process is passive and no physical markers are needed on the person's face. Models produced by our method are suited to realistic animations of specific individuals for applications in special effects, games, and 3D teleconferencing. 1. Introduction Ever since the pioneering work of Frederic I. Parke [1] in 1972, researchers have attempted to generate realistic facial models and animation. Recent inte... | [
1437
] | Test |
970 | 4 | Learning Hierarchical Task Models by Defining and Refining Examples Task models are used in many areas of computer science including planning, intelligent tutoring, plan recognition, interface design, and decision theory. However, developing task models is a significant practical challenge. We present a task model development environment centered around a machine learning engine that infers task models from examples. A novel aspect of the environment is support for a domain expert to refine past examples as he or she develops a clearer understanding of how to model the domain. Collectively, these examples constitute a "test suite" that the development environment manages in order to verify that manual changes to the evolving task model do not have unintended consequences. 1. | [
109
] | Train |
971 | 2 | Vector-Based Natural Language Call Routing This paper describes a domain independent, automatically trained natural language call router for directing incoming calls in a call center. Our call router directs customer calls based on their response to an open-ended "How may I direct your call?" prompt. Routing behavior is trained from a corpus of transcribed and hand-routed calls and then carried out using vectorbased information retrieval techniques. Terms consist of n-gram sequences of morphologically reduced content words, while documents representing routing destinations consists of weighted term frequencies derived from calls to that destination in the training corpus. Based on the statistical discriminating power of the n-gram terms extracted from the caller's request, the caller is 1) routed to the appropriate destination, 2) transferred to a human operator, or 3) asked a disambiguation question. In the last case, the system dynamically generates queries tailored to the caller's request and the destinations with which it is consistent, based on our extension of the vector model. Evaluation of the call router performance over a financial services call center using both accurate transcriptions of calls and fairly noisy speech recognizer output demonstrated robustness in the face of speech recognition errors. Furthermore, our system showed a substantial improvement in performance over existing systems by correctly routing 93.8% of the calls after punting 10.2% of all calls to a human operator on transcription, with approximately 4% degradation in performance when using speech recognizer output with a 23% word error rate. | [
407
] | Train |
972 | 1 | Glove-TalkII: A neural network interface which maps gestures to parallel formant speech synthesizer controls Glove-TalkII is a system which translates hand gestures to speech through an adaptive interface. Hand gestures are mapped continuously to 10 control parameters of a parallel formant speech synthesizer. The mapping allows the hand to act as an artificial vocal tract that produces speech in real time. This gives an unlimited vocabulary in addition to direct control of fundamental frequency and volume. Currently, the best version of GloveTalkII uses several input devices (including a Cyberglove, a ContactGlove, a 3-space tracker, and a foot-pedal), a parallel formant speech synthesizer and 3 neural networks. The gesture-to-speech task is divided into vowel and consonant production by using a gating network to weight the outputs of a vowel and a consonant neural network. The gating network and the consonant network are trained with examples from the user. The vowel network implements a fixed, user-defined relationship between hand-position and vowel sound and does not require any training ... | [
2001
] | Train |
973 | 1 | An Open Software Infrastructure For Reconfigurable Control Systems Recent advances in software technology have the potential to revolutionize control system design. This paper describes a new software infrastructure for complex control systems, which exploits new and emerging software technologies. It presents an open control platform (OCP) for complex systems, including those that must be reconfigured or customized in real-time for extreme-performance applications. An application of the OCP to the control system design of an autonomous aerial vehicle is described. 1 Introduction Complex dynamic systems, such as aircraft, power systems, and telecommunications networks, present major challenges to control systems designers. Both the military and civilian sectors of our economy are demanding new and highly sophisticated capabilities from these systems that the current state-of-the-art is not offering. Among them are the following: . Ability to adapt to a changing environment; . Ability to reconfigure the control algorithms; . Plug-and-play exten... | [
2167
] | Validation |
974 | 4 | An Anthropomorphic Agent for the Use of Spatial Language . In this paper we describe the communication with a responsive virtual environment with the main emphasis on the processing of spatial expressions in natural language instructions. This work is part of the VIENA project in whichwechose interior design as an example domain. A multiagent system acts as an intelligent mediator between the user and a graphics system. To make the communication about spatial relations more intuitive, we developed an anthropomorphic agent which is graphically visualized in the scene. Considering the human-like #gure we explain the use of qualitative spatial expressions, like #right of " and #there". 1 Introduction Interactive 3-dimensional graphics systems are more useful #e.g. in design#, when users can concentrate on their imaginations and be free from technical considerations. Therefore it is important to improveinteraction with the virtual environmentbyway of natural, intuitive communication forms. In our work we consider a #virtual interface... | [
203
] | Test |
975 | 3 | Active Rule Analysis And Optimisation In The Rock & Roll Deductive Object-Oriented Database Active database systems provide facilities that monitor and respond to changes of relevance to the database. Active behaviour is normally described using Event Condition Action rules (ECA-rules), and a number of systems have been developed, based upon different data models, that support such rules. However, experience using active databases shows that while such systems are powerful and potentially useful in many applications, they are hard to program and liable to exhibit poor performance at runtime. This document addresses both of these issues by examining both analysis and optimisation of active rules in the context of a powerful active database system. It is shown how rule analysis methods developed for straightforward active rule languages for relational data models can be extended to take account of rich event description languages and more powerful execution models. It is also shown how the results of analyses can be exploited by rule optimisers, and that multiple quer... | [
1691
] | Test |
976 | 2 | Towards a Highly-Scalable and Effective Metasearch Engine A metasearch engine is a system that supports unified access to multiple local search engines. Database selection is one of the main challenges in building a large-scale metasearch engine. The problem is to efficiently and accurately determine a small number of potentially useful local search engines to invoke for each user query. In order to enable accurate selection, metadata that reect the contents of each search engine need to be collected and used. In this paper, we propose a highly scalable and accurate database selection method. This method has several novel features. First, the metadata for representing the contents of all search engines are organized into a single integrated representative. Such a representative yields both computation efficiency and storage efficiency. Second, our selection method is based on a theory for ranking search engines optimally. Experimental results indicate that this new method is very effective. An operational prototype system has been built based on the proposed approach. | [
347,
488,
521,
587,
1059,
1134,
1642,
1888,
2275,
2464,
2822,
2920
] | Train |
977 | 2 | Word Sense Disambiguation And Its Application To Internet Search ambiguation method presented here is that it provides a ranking of possible associations between words senses, rather than a binary yes/no decision for a possible sense combination. This proves to be particularly useful for Natural Language Processing tasks such as retrieving information related to a particular input question. An important task which can highly benet from a Word Sense Disambiguation method is the Internet search. This thesis presents a possible application of Word Sense Disambiguation techniques for improving the quality of the search on the Internet. Knowing the sense of the words in the input question enables the creation of similarity lists which contain words semantically related to the original keywords, and which can be further used for query extension. The extended query, together with the new lexical operators dened for information extraction, improve both the precision and the resolution of a search on the Internet. iv Speci | [
363
] | Validation |
978 | 0 | Representing Coordination Relationships with Influence Diagrams It is well know the necessity of managing relationships among agents in a multi-agent system to achieve coordinated behavior. One approach to manage such relationships consists of using an explicit representation of them, allowing each agent to choose its actions based on them. Previous work in the area have considered ideal situations, such as fully known environments, static relationships and shared mental states. In this paper we propose to represent relationships among agents and entities in a multi-agent system by using influence diagrams. | [
1107,
1115,
1518,
2173,
2635,
2883
] | Test |
979 | 1 | A Simple Neural Network Models Categorical Perception of Facial Expressions The performance of a neural network that categorizes facial expressions is compared with human subjects over a set of experiments using interpolated imagery. The experiments for both the human subjects and neural networks make use of interpolations of facial expressions from the Pictures of Facial Affect Database [Ekman and Friesen, 1976]. The only difference in materials between those used in the human subjects experiments [Young et al., 1997] and our materials are the manner in which the interpolated images are constructed -- image-quality morphs versus pixel averages. Nevertheless, the neural network accurately captures the categorical nature of the human responses, showing sharp transitions in labeling of images along the interpolated sequence. Crucially for a demonstration of categorical perception [Harnad, 1987], the model shows the highest discrimination between transition images at the crossover point. The model also captures the shape of the reaction time curves of the human s... | [
163
] | Train |
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