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cs/0310011
Re-Finding Found Things: An Exploratory Study of How Users Re-Find Information
cs.HC cs.IR
The problem of how people find information is studied extensively; however, the problem of how people organize, re-use, and re-find information that they have found is not as well understood. Recently, several projects have conducted in-situ studies to explore how people re-find and re-use information. Here, we present results and observations from a controlled, laboratory study of refinding information found on the web. Our study was conducted as a collaborative exercise with pairs of participants. One participant acted as a retriever, helping the other participant re-find information by telephone. This design allowed us to gain insight into the strategies that users employed to re-find information, and into how domain artifacts and contextual information were used to aid the re-finding process. We also introduced the ability for users to add their own explicitly artifacts in the form of making annotations on the web pages they viewed. We observe that re-finding often occurs as a two stage, iterative process in which users first attempt to locate an information source (search), and once found, begin a process to find the specific information being sought (browse). Our findings are consistent with research on waypoints; orienteering approaches to re-finding; and navigation of electronic spaces. Furthermore, we observed that annotations were utilized extensively, indicating that explicitly added context by the user can play an important role in re-finding.
cs/0310012
A Formal Comparison of Visual Web Wrapper Generators
cs.DB
We study the core fragment of the Elog wrapping language used in the Lixto system (a visual wrapper generator) and formally compare Elog to other wrapping languages proposed in the literature.
cs/0310013
WebTeach in practice: the entrance test to the Engineering faculty in Florence
cs.HC cs.IR
We present the WebTeach project, formed by a web interface to database for test management, a wiki site for the diffusion of teaching material and student forums, and a suite for the generation of multiple-choice mathematical quiz with automatic elaboration of forms. This system has been massively tested for the entrance test to the Engineering Faculty of the University of Florence, Italy
cs/0310014
Effective XML Representation for Spoken Language in Organisations
cs.CL
Spoken Language can be used to provide insights into organisational processes, unfortunately transcription and coding stages are very time consuming and expensive. The concept of partial transcription and coding is proposed in which spoken language is indexed prior to any subsequent processing. The functional linguistic theory of texture is used to describe the effects of partial transcription on observational records. The standard used to encode transcript context and metadata is called CHAT, but a previous XML schema developed to implement it contains design assumptions that make it difficult to support partial transcription for example. This paper describes a more effective XML schema that overcomes many of these problems and is intended for use in applications that support the rapid development of spoken language deliverables.
cs/0310018
The Study of the Application of a Keywords-based Chatbot System on the Teaching of Foreign Languages
cs.CY cs.CL
This paper reports the findings of a study conducted on the application of an on-line human-computer dialog system with natural language (chatbot) on the teaching of foreign languages. A keywords-based human-computer dialog system makes it possible that the user could chat with the computer using a natural language, i.e. in English or in German to some extent. So an experiment has been made using this system online to work as a chat partner with the users learning the foreign languages. Dialogs between the users and the chatbot are collected. Findings indicate that the dialogs between the human and the computer are mostly very short because the user finds the responses from the computer are mostly repeated and irrelevant with the topics and context and the program does not understand the language at all. With analysis of the keywords or pattern-matching mechanism used in this chatbot it can be concluded that this kind of system can not work as a teaching assistant program in foreign language learning.
cs/0310021
Fuzzy Relational Modeling of Cost and Affordability for Advanced Technology Manufacturing Environment
cs.CE cs.AI math.OC
Relational representation of knowledge makes it possible to perform all the computations and decision making in a uniform relational way by means of special relational compositions called triangle and square products. In this paper some applications in manufacturing related to cost analysis are described. Testing fuzzy relational structures for various relational properties allows us to discover dependencies, hierarchies, similarities, and equivalences of the attributes characterizing technological processes and manufactured artifacts in their relationship to costs and performance. A brief overview of mathematical aspects of BK-relational products is given in Appendix 1 together with further references in the literature.
cs/0310023
Application of Kullback-Leibler Metric to Speech Recognition
cs.AI
Article discusses the application of Kullback-Leibler divergence to the recognition of speech signals and suggests three algorithms implementing this divergence criterion: correlation algorithm, spectral algorithm and filter algorithm. Discussion covers an approach to the problem of speech variability and is illustrated with the results of experimental modeling of speech signals. The article gives a number of recommendations on the choice of appropriate model parameters and provides a comparison to some other methods of speech recognition.
cs/0310028
Providing Diversity in K-Nearest Neighbor Query Results
cs.DB
Given a point query Q in multi-dimensional space, K-Nearest Neighbor (KNN) queries return the K closest answers according to given distance metric in the database with respect to Q. In this scenario, it is possible that a majority of the answers may be very similar to some other, especially when the data has clusters. For a variety of applications, such homogeneous result sets may not add value to the user. In this paper, we consider the problem of providing diversity in the results of KNN queries, that is, to produce the closest result set such that each answer is sufficiently different from the rest. We first propose a user-tunable definition of diversity, and then present an algorithm, called MOTLEY, for producing a diverse result set as per this definition. Through a detailed experimental evaluation on real and synthetic data, we show that MOTLEY can produce diverse result sets by reading only a small fraction of the tuples in the database. Further, it imposes no additional overhead on the evaluation of traditional KNN queries, thereby providing a seamless interface between diversity and distance.
cs/0310035
Supporting Exploratory Queries in Database Centric Web Applications
cs.DB
Users of database-centric Web applications, especially in the e-commerce domain, often resort to exploratory ``trial-and-error'' queries since the underlying data space is huge and unfamiliar, and there are several alternatives for search attributes in this space. For example, scouting for cheap airfares typically involves posing multiple queries, varying flight times, dates, and airport locations. Exploratory queries are problematic from the perspective of both the user and the server. For the database server, it results in a drastic reduction in effective throughput since much of the processing is duplicated in each successive query. For the client, it results in a marked increase in response times, especially when accessing the service through wireless channels. In this paper, we investigate the design of automated techniques to minimize the need for repetitive exploratory queries. Specifically, we present SAUNA, a server-side query relaxation algorithm that, given the user's initial range query and a desired cardinality for the answer set, produces a relaxed query that is expected to contain the required number of answers. The algorithm incorporates a range-query-specific distance metric that is weighted to produce relaxed queries of a desired shape (e.g. aspect ratio preserving), and utilizes multi-dimensional histograms for query size estimation. A detailed performance evaluation of SAUNA over a variety of multi-dimensional data sets indicates that its relaxed queries can significantly reduce the costs associated with exploratory query processing.
cs/0310038
On Addressing Efficiency Concerns in Privacy Preserving Data Mining
cs.DB
Data mining services require accurate input data for their results to be meaningful, but privacy concerns may influence users to provide spurious information. To encourage users to provide correct inputs, we recently proposed a data distortion scheme for association rule mining that simultaneously provides both privacy to the user and accuracy in the mining results. However, mining the distorted database can be orders of magnitude more time-consuming as compared to mining the original database. In this paper, we address this issue and demonstrate that by (a) generalizing the distortion process to perform symbol-specific distortion, (b) appropriately choosing the distortion parameters, and (c) applying a variety of optimizations in the reconstruction process, runtime efficiencies that are well within an order of magnitude of undistorted mining can be achieved.
cs/0310041
A Dynamic Programming Algorithm for the Segmentation of Greek Texts
cs.CL cs.DL
In this paper we introduce a dynamic programming algorithm to perform linear text segmentation by global minimization of a segmentation cost function which consists of: (a) within-segment word similarity and (b) prior information about segment length. The evaluation of the segmentation accuracy of the algorithm on a text collection consisting of Greek texts showed that the algorithm achieves high segmentation accuracy and appears to be very innovating and promissing.
cs/0310043
Value-at-Risk and Expected Shortfall for Quadratic portfolio of securities with mixture of elliptic Distributed Risk Factors
cs.CE math.CA
Generally, in the financial literature, the notion of quadratic VaR is implicitly confused with the Delta-Gamma VaR, because more authors dealt with portfolios that contains derivatives instruments. In this paper, we postpone to estimate the Value-at-Risk of a quadratic portfolio of securities (i.e equities) without the Delta and Gamma greeks, when the joint log-returns changes with multivariate elliptic distribution. We have reduced the estimation of the quadratic VaR of such portfolio to a resolution of one dimensional integral equation. To illustrate our method, we give special attention to the mixture of normal and mixture of t-student distribution. For given VaR, when joint Risk Factors changes with elliptic distribution, we show how to estimate an Expected Shortfall .
cs/0310044
The Algebra of Utility Inference
cs.AI
Richard Cox [1] set the axiomatic foundations of probable inference and the algebra of propositions. He showed that consistency within these axioms requires certain rules for updating belief. In this paper we use the analogy between probability and utility introduced in [2] to propose an axiomatic foundation for utility inference and the algebra of preferences. We show that consistency within these axioms requires certain rules for updating preference. We discuss a class of utility functions that stems from the axioms of utility inference and show that this class is the basic building block for any general multiattribute utility function. We use this class of utility functions together with the algebra of preferences to construct utility functions represented by logical operations on the attributes.
cs/0310045
An information theory for preferences
cs.AI
Recent literature in the last Maximum Entropy workshop introduced an analogy between cumulative probability distributions and normalized utility functions. Based on this analogy, a utility density function can de defined as the derivative of a normalized utility function. A utility density function is non-negative and integrates to unity. These two properties form the basis of a correspondence between utility and probability. A natural application of this analogy is a maximum entropy principle to assign maximum entropy utility values. Maximum entropy utility interprets many of the common utility functions based on the preference information needed for their assignment, and helps assign utility values based on partial preference information. This paper reviews maximum entropy utility and introduces further results that stem from the duality between probability and utility.
cs/0310047
Abductive Logic Programs with Penalization: Semantics, Complexity and Implementation
cs.AI
Abduction, first proposed in the setting of classical logics, has been studied with growing interest in the logic programming area during the last years. In this paper we study abduction with penalization in the logic programming framework. This form of abductive reasoning, which has not been previously analyzed in logic programming, turns out to represent several relevant problems, including optimization problems, very naturally. We define a formal model for abduction with penalization over logic programs, which extends the abductive framework proposed by Kakas and Mancarella. We address knowledge representation issues, encoding a number of problems in our abductive framework. In particular, we consider some relevant problems, taken from different domains, ranging from optimization theory to diagnosis and planning; their encodings turn out to be simple and elegant in our formalism. We thoroughly analyze the computational complexity of the main problems arising in the context of abduction with penalization from logic programs. Finally, we implement a system supporting the proposed abductive framework on top of the DLV engine. To this end, we design a translation from abduction problems with penalties into logic programs with weak constraints. We prove that this approach is sound and complete.
cs/0310048
Managing Evolving Business Workflows through the Capture of Descriptive Information
cs.SE cs.DB
Business systems these days need to be agile to address the needs of a changing world. In particular the discipline of Enterprise Application Integration requires business process management to be highly reconfigurable with the ability to support dynamic workflows, inter-application integration and process reconfiguration. Basing EAI systems on model-resident or on a so-called description-driven approach enables aspects of flexibility, distribution, system evolution and integration to be addressed in a domain-independent manner. Such a system called CRISTAL is described in this paper with particular emphasis on its application to EAI problem domains. A practical example of the CRISTAL technology in the domain of manufacturing systems, called Agilium, is described to demonstrate the principles of model-driven system evolution and integration. The approach is compared to other model-driven development approaches such as the Model-Driven Architecture of the OMG and so-called Adaptive Object Models.
cs/0310050
Feedforward Neural Networks with Diffused Nonlinear Weight Functions
cs.NE
In this paper, feedforward neural networks are presented that have nonlinear weight functions based on look--up tables, that are specially smoothed in a regularization called the diffusion. The idea of such a type of networks is based on the hypothesis that the greater number of adaptive parameters per a weight function might reduce the total number of the weight functions needed to solve a given problem. Then, if the computational complexity of a propagation through a single such a weight function would be kept low, then the introduced neural networks might possibly be relatively fast. A number of tests is performed, showing that the presented neural networks may indeed perform better in some cases than the classic neural networks and a number of other learning machines.
cs/0310058
Application Architecture for Spoken Language Resources in Organisational Settings
cs.CL
Special technologies need to be used to take advantage of, and overcome, the challenges associated with acquiring, transforming, storing, processing, and distributing spoken language resources in organisations. This paper introduces an application architecture consisting of tools and supporting utilities for indexing and transcription, and describes how these tools, together with downstream processing and distribution systems, can be integrated into a workflow. Two sample applications for this architecture are outlined- the analysis of decision-making processes in organisations and the deployment of systems development methods by designers in the field.
cs/0310061
Local-search techniques for propositional logic extended with cardinality constraints
cs.AI
We study local-search satisfiability solvers for propositional logic extended with cardinality atoms, that is, expressions that provide explicit ways to model constraints on cardinalities of sets. Adding cardinality atoms to the language of propositional logic facilitates modeling search problems and often results in concise encodings. We propose two ``native'' local-search solvers for theories in the extended language. We also describe techniques to reduce the problem to standard propositional satisfiability and allow us to use off-the-shelf SAT solvers. We study these methods experimentally. Our general finding is that native solvers designed specifically for the extended language perform better than indirect methods relying on SAT solvers.
cs/0310062
WSAT(cc) - a fast local-search ASP solver
cs.AI
We describe WSAT(cc), a local-search solver for computing models of theories in the language of propositional logic extended by cardinality atoms. WSAT(cc) is a processing back-end for the logic PS+, a recently proposed formalism for answer-set programming.
cs/0311001
Modeling State in Software Debugging of VHDL-RTL Designs -- A Model-Based Diagnosis Approach
cs.AI cs.SE
In this paper we outline an approach of applying model-based diagnosis to the field of automatic software debugging of hardware designs. We present our value-level model for debugging VHDL-RTL designs and show how to localize the erroneous component responsible for an observed misbehavior. Furthermore, we discuss an extension of our model that supports the debugging of sequential circuits, not only at a given point in time, but also allows for considering the temporal behavior of VHDL-RTL designs. The introduced model is capable of handling state inherently present in every sequential circuit. The principal applicability of the new model is outlined briefly and we use industrial-sized real world examples from the ISCAS'85 benchmark suite to discuss the scalability of our approach.
cs/0311003
Enhancing a Search Algorithm to Perform Intelligent Backtracking
cs.AI cs.LO
This paper illustrates how a Prolog program, using chronological backtracking to find a solution in some search space, can be enhanced to perform intelligent backtracking. The enhancement crucially relies on the impurity of Prolog that allows a program to store information when a dead end is reached. To illustrate the technique, a simple search program is enhanced. To appear in Theory and Practice of Logic Programming. Keywords: intelligent backtracking, dependency-directed backtracking, backjumping, conflict-directed backjumping, nogood sets, look-back.
cs/0311004
Utility-Probability Duality
cs.AI
This paper presents duality between probability distributions and utility functions.
cs/0311007
Parametric Connectives in Disjunctive Logic Programming
cs.AI
Disjunctive Logic Programming (\DLP) is an advanced formalism for Knowledge Representation and Reasoning (KRR). \DLP is very expressive in a precise mathematical sense: it allows to express every property of finite structures that is decidable in the complexity class $\SigmaP{2}$ ($\NP^{\NP}$). Importantly, the \DLP encodings are often simple and natural. In this paper, we single out some limitations of \DLP for KRR, which cannot naturally express problems where the size of the disjunction is not known ``a priori'' (like N-Coloring), but it is part of the input. To overcome these limitations, we further enhance the knowledge modelling abilities of \DLP, by extending this language by {\em Parametric Connectives (OR and AND)}. These connectives allow us to represent compactly the disjunction/conjunction of a set of atoms having a given property. We formally define the semantics of the new language, named $DLP^{\bigvee,\bigwedge}$ and we show the usefulness of the new constructs on relevant knowledge-based problems. We address implementation issues and discuss related works.
cs/0311008
A Parameterised Hierarchy of Argumentation Semantics for Extended Logic Programming and its Application to the Well-founded Semantics
cs.LO cs.AI
Argumentation has proved a useful tool in defining formal semantics for assumption-based reasoning by viewing a proof as a process in which proponents and opponents attack each others arguments by undercuts (attack to an argument's premise) and rebuts (attack to an argument's conclusion). In this paper, we formulate a variety of notions of attack for extended logic programs from combinations of undercuts and rebuts and define a general hierarchy of argumentation semantics parameterised by the notions of attack chosen by proponent and opponent. We prove the equivalence and subset relationships between the semantics and examine some essential properties concerning consistency and the coherence principle, which relates default negation and explicit negation. Most significantly, we place existing semantics put forward in the literature in our hierarchy and identify a particular argumentation semantics for which we prove equivalence to the paraconsistent well-founded semantics with explicit negation, WFSX$_p$. Finally, we present a general proof theory, based on dialogue trees, and show that it is sound and complete with respect to the argumentation semantics.
cs/0311011
On an explicit finite difference method for fractional diffusion equations
cs.NA cond-mat.stat-mech cs.CE physics.comp-ph
A numerical method to solve the fractional diffusion equation, which could also be easily extended to many other fractional dynamics equations, is considered. These fractional equations have been proposed in order to describe anomalous transport characterized by non-Markovian kinetics and the breakdown of Fick's law. In this paper we combine the forward time centered space (FTCS) method, well known for the numerical integration of ordinary diffusion equations, with the Grunwald-Letnikov definition of the fractional derivative operator to obtain an explicit fractional FTCS scheme for solving the fractional diffusion equation. The resulting method is amenable to a stability analysis a la von Neumann. We show that the analytical stability bounds are in excellent agreement with numerical tests. Comparison between exact analytical solutions and numerical predictions are made.
cs/0311012
A rigorous definition of axial lines: ridges on isovist fields
cs.CV cs.CG
We suggest that 'axial lines' defined by (Hillier and Hanson, 1984) as lines of uninterrupted movement within urban streetscapes or buildings, appear as ridges in isovist fields (Benedikt, 1979). These are formed from the maximum diametric lengths of the individual isovists, sometimes called viewsheds, that make up these fields (Batty and Rana, 2004). We present an image processing technique for the identification of lines from ridges, discuss current strengths and weaknesses of the method, and show how it can be implemented easily and effectively.
cs/0311014
Optimality of Universal Bayesian Sequence Prediction for General Loss and Alphabet
cs.LG cs.AI math.PR
Various optimality properties of universal sequence predictors based on Bayes-mixtures in general, and Solomonoff's prediction scheme in particular, will be studied. The probability of observing $x_t$ at time $t$, given past observations $x_1...x_{t-1}$ can be computed with the chain rule if the true generating distribution $\mu$ of the sequences $x_1x_2x_3...$ is known. If $\mu$ is unknown, but known to belong to a countable or continuous class $\M$ one can base ones prediction on the Bayes-mixture $\xi$ defined as a $w_\nu$-weighted sum or integral of distributions $\nu\in\M$. The cumulative expected loss of the Bayes-optimal universal prediction scheme based on $\xi$ is shown to be close to the loss of the Bayes-optimal, but infeasible prediction scheme based on $\mu$. We show that the bounds are tight and that no other predictor can lead to significantly smaller bounds. Furthermore, for various performance measures, we show Pareto-optimality of $\xi$ and give an Occam's razor argument that the choice $w_\nu\sim 2^{-K(\nu)}$ for the weights is optimal, where $K(\nu)$ is the length of the shortest program describing $\nu$. The results are applied to games of chance, defined as a sequence of bets, observations, and rewards. The prediction schemes (and bounds) are compared to the popular predictors based on expert advice. Extensions to infinite alphabets, partial, delayed and probabilistic prediction, classification, and more active systems are briefly discussed.
cs/0311015
Make search become the internal function of Internet
cs.IR cs.DL cs.NI
Domain Resource Integrated System (DRIS) is introduced in this paper. DRIS is a distributed information retrieval system, which will solve problems like poor coverage, long update interval in current web search system. The most distinct character of DRIS is that it's a public opening system, and acts as an internal component of Internet, but not the production of a company. The implementation of DRIS is also represented.
cs/0311019
Replay Debugging of Complex Real-Time Systems: Experiences from Two Industrial Case Studies
cs.RO
Deterministic replay is a method for allowing complex multitasking real-time systems to be debugged using standard interactive debuggers. Even though several replay techniques have been proposed for parallel, multi-tasking and real-time systems, the solutions have so far lingered on a prototype academic level, with very little results to show from actual state-of-the-practice commercial applications. This paper describes a major deterministic replay debugging case study performed on a full-scale industrial robot control system, as well as a minor replay instrumentation case study performed on a military aircraft radar system. In this article, we will show that replay debugging is feasible in complex multi-million lines of code software projects running on top of off-the-shelf real-time operating systems. Furthermore, we will discuss how replay debugging can be introduced in existing systems without impracticable analysis efforts. In addition, we will present benchmarking results from both studies, indicating that the instrumentation overhead is acceptable and affordable.
cs/0311024
Logic-Based Specification Languages for Intelligent Software Agents
cs.AI
The research field of Agent-Oriented Software Engineering (AOSE) aims to find abstractions, languages, methodologies and toolkits for modeling, verifying, validating and prototyping complex applications conceptualized as Multiagent Systems (MASs). A very lively research sub-field studies how formal methods can be used for AOSE. This paper presents a detailed survey of six logic-based executable agent specification languages that have been chosen for their potential to be integrated in our ARPEGGIO project, an open framework for specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each executable language, the logic foundations are described and an example of use is shown. A comparison of the six languages and a survey of similar approaches complete the paper, together with considerations of the advantages of using logic-based languages in MAS modeling and prototyping.
cs/0311026
Great Expectations. Part I: On the Customizability of Generalized Expected Utility
cs.AI
We propose a generalization of expected utility that we call generalized EU (GEU), where a decision maker's beliefs are represented by plausibility measures, and the decision maker's tastes are represented by general (i.e.,not necessarily real-valued) utility functions. We show that every agent, ``rational'' or not, can be modeled as a GEU maximizer. We then show that we can customize GEU by selectively imposing just the constraints we want. In particular, we show how each of Savage's postulates corresponds to constraints on GEU.
cs/0311027
Great Expectations. Part II: Generalized Expected Utility as a Universal Decision Rule
cs.AI
Many different rules for decision making have been introduced in the literature. We show that a notion of generalized expected utility proposed in Part I of this paper is a universal decision rule, in the sense that it can represent essentially all other decision rules.
cs/0311028
Using Counterfactuals in Knowledge-Based Programming
cs.DC cs.AI
This paper adds counterfactuals to the framework of knowledge-based programs of Fagin, Halpern, Moses, and Vardi. The use of counterfactuals is illustrated by designing a protocol in which an agent stops sending messages once it knows that it is safe to do so. Such behavior is difficult to capture in the original framework because it involves reasoning about counterfactual executions, including ones that are not consistent with the protocol. Attempts to formalize these notions without counterfactuals are shown to lead to rather counterintuitive behavior.
cs/0311029
Staging Transformations for Multimodal Web Interaction Management
cs.IR cs.PL
Multimodal interfaces are becoming increasingly ubiquitous with the advent of mobile devices, accessibility considerations, and novel software technologies that combine diverse interaction media. In addition to improving access and delivery capabilities, such interfaces enable flexible and personalized dialogs with websites, much like a conversation between humans. In this paper, we present a software framework for multimodal web interaction management that supports mixed-initiative dialogs between users and websites. A mixed-initiative dialog is one where the user and the website take turns changing the flow of interaction. The framework supports the functional specification and realization of such dialogs using staging transformations -- a theory for representing and reasoning about dialogs based on partial input. It supports multiple interaction interfaces, and offers sessioning, caching, and co-ordination functions through the use of an interaction manager. Two case studies are presented to illustrate the promise of this approach.
cs/0311031
Towards an Intelligent Database System Founded on the SP Theory of Computing and Cognition
cs.DB cs.AI
The SP theory of computing and cognition, described in previous publications, is an attractive model for intelligent databases because it provides a simple but versatile format for different kinds of knowledge, it has capabilities in artificial intelligence, and it can also function like established database models when that is required. This paper describes how the SP model can emulate other models used in database applications and compares the SP model with those other models. The artificial intelligence capabilities of the SP model are reviewed and its relationship with other artificial intelligence systems is described. Also considered are ways in which current prototypes may be translated into an 'industrial strength' working system.
cs/0311033
The Rank-Frequency Analysis for the Functional Style Corpora in the Ukrainian Language
cs.CL
We use the rank-frequency analysis for the estimation of Kernel Vocabulary size within specific corpora of Ukrainian. The extrapolation of high-rank behaviour is utilized for estimation of the total vocabulary size.
cs/0311036
Measuring the Functional Load of Phonological Contrasts
cs.CL
Frequency counts are a measure of how much use a language makes of a linguistic unit, such as a phoneme or word. However, what is often important is not the units themselves, but the contrasts between them. A measure is therefore needed for how much use a language makes of a contrast, i.e. the functional load (FL) of the contrast. We generalize previous work in linguistics and speech recognition and propose a family of measures for the FL of several phonological contrasts, including phonemic oppositions, distinctive features, suprasegmentals, and phonological rules. We then test it for robustness to changes of corpora. Finally, we provide examples in Cantonese, Dutch, English, German and Mandarin, in the context of historical linguistics, language acquisition and speech recognition. More information can be found at http://dinoj.info/research/fload
cs/0311038
XPath-Logic and XPathLog: A Logic-Programming Style XML Data Manipulation Language
cs.DB
We define XPathLog as a Datalog-style extension of XPath. XPathLog provides a clear, declarative language for querying and manipulating XML whose perspectives are especially in XML data integration. In our characterization, the formal semantics is defined wrt. an edge-labeled graph-based model which covers the XML data model. We give a complete, logic-based characterization of XML data and the main language concept for XML, XPath. XPath-Logic extends the XPath language with variable bindings and embeds it into first-order logic. XPathLog is then the Horn fragment of XPath-Logic, providing a Datalog-style, rule-based language for querying and manipulating XML data. The model-theoretic semantics of XPath-Logic serves as the base of XPathLog as a logic-programming language, whereas also an equivalent answer-set semantics for evaluating XPathLog queries is given. In contrast to other approaches, the XPath syntax and semantics is also used for a declarative specification how the database should be updated: when used in rule heads, XPath filters are interpreted as specifications of elements and properties which should be added to the database.
cs/0311041
S-ToPSS: Semantic Toronto Publish/Subscribe System
cs.DC cs.DB
The increase in the amount of data on the Internet has led to the development of a new generation of applications based on selective information dissemination where, data is distributed only to interested clients. Such applications require a new middleware architecture that can efficiently match user interests with available information. Middleware that can satisfy this requirement include event-based architectures such as publish-subscribe systems. In this demonstration paper we address the problem of semantic matching. We investigate how current publish/subscribe systems can be extended with semantic capabilities. Our main contribution is the development and validation (through demonstration) of a semantic pub/sub system prototype S-ToPSS (Semantic Toronto Publish/Subscribe System).
cs/0311042
Toward Attribute Efficient Learning Algorithms
cs.LG
We make progress on two important problems regarding attribute efficient learnability. First, we give an algorithm for learning decision lists of length $k$ over $n$ variables using $2^{\tilde{O}(k^{1/3})} \log n$ examples and time $n^{\tilde{O}(k^{1/3})}$. This is the first algorithm for learning decision lists that has both subexponential sample complexity and subexponential running time in the relevant parameters. Our approach establishes a relationship between attribute efficient learning and polynomial threshold functions and is based on a new construction of low degree, low weight polynomial threshold functions for decision lists. For a wide range of parameters our construction matches a 1994 lower bound due to Beigel for the ODDMAXBIT predicate and gives an essentially optimal tradeoff between polynomial threshold function degree and weight. Second, we give an algorithm for learning an unknown parity function on $k$ out of $n$ variables using $O(n^{1-1/k})$ examples in time polynomial in $n$. For $k=o(\log n)$ this yields a polynomial time algorithm with sample complexity $o(n)$. This is the first polynomial time algorithm for learning parity on a superconstant number of variables with sublinear sample complexity.
cs/0311045
Unsupervised Grammar Induction in a Framework of Information Compression by Multiple Alignment, Unification and Search
cs.AI
This paper describes a novel approach to grammar induction that has been developed within a framework designed to integrate learning with other aspects of computing, AI, mathematics and logic. This framework, called "information compression by multiple alignment, unification and search" (ICMAUS), is founded on principles of Minimum Length Encoding pioneered by Solomonoff and others. Most of the paper describes SP70, a computer model of the ICMAUS framework that incorporates processes for unsupervised learning of grammars. An example is presented to show how the model can infer a plausible grammar from appropriate input. Limitations of the current model and how they may be overcome are briefly discussed.
cs/0311047
I know what you mean: semantic issues in Internet-scale publish/subscribe systems
cs.DC cs.DB
In recent years, the amount of information on the Internet has increased exponentially developing great interest in selective information dissemination systems. The publish/subscribe paradigm is particularly suited for designing systems for routing information and requests according to their content throughout wide-area network of brokers. Current publish/subscribe systems use limited syntax-based content routing but since publishers and subscribers are anonymous and decoupled in time, space and location, often over wide-area network boundary, they do not necessarily speak the same language. Consequently, adding semantics to current publish/subscribe systems is important. In this paper we identify and examine the issues in developing semantic-based content routing for publish/subscribe broker networks.
cs/0311048
Turning CARTwheels: An Alternating Algorithm for Mining Redescriptions
cs.CE cs.AI
We present an unusual algorithm involving classification trees where two trees are grown in opposite directions so that they are matched at their leaves. This approach finds application in a new data mining task we formulate, called "redescription mining". A redescription is a shift-of-vocabulary, or a different way of communicating information about a given subset of data; the goal of redescription mining is to find subsets of data that afford multiple descriptions. We highlight the importance of this problem in domains such as bioinformatics, which exhibit an underlying richness and diversity of data descriptors (e.g., genes can be studied in a variety of ways). Our approach helps integrate multiple forms of characterizing datasets, situates the knowledge gained from one dataset in the context of others, and harnesses high-level abstractions for uncovering cryptic and subtle features of data. Algorithm design decisions, implementation details, and experimental results are presented.
cs/0311050
Data mining and Privacy in Public Sector using Intelligent Agents (discussion paper)
cs.CY cs.AI cs.IR cs.MA
The public sector comprises government agencies, ministries, education institutions, health providers and other types of government, commercial and not-for-profit organisations. Unlike commercial enterprises, this environment is highly heterogeneous in all aspects. This forms a complex network which is not always optimised. A lack of optimisation and communication hinders information sharing between the network nodes limiting the flow of information. Another limiting aspect is privacy of personal information and security of operations of some nodes or segments of the network. Attempts to reorganise the network or improve communications to make more information available for sharing and analysis may be hindered or completely halted by public concerns over privacy, political agendas, social and technological barriers. This paper discusses a technical solution for information sharing while addressing the privacy concerns with no need for reorganisation of the existing public sector infrastructure . The solution is based on imposing an additional layer of Intelligent Software Agents and Knowledge Bases for data mining and analysis.
cs/0311051
Integrating existing cone-shaped and projection-based cardinal direction relations and a TCSP-like decidable generalisation
cs.AI
We consider the integration of existing cone-shaped and projection-based calculi of cardinal direction relations, well-known in QSR. The more general, integrating language we consider is based on convex constraints of the qualitative form $r(x,y)$, $r$ being a cone-shaped or projection-based cardinal direction atomic relation, or of the quantitative form $(\alpha ,\beta)(x,y)$, with $\alpha ,\beta\in [0,2\pi)$ and $(\beta -\alpha)\in [0,\pi ]$: the meaning of the quantitative constraint, in particular, is that point $x$ belongs to the (convex) cone-shaped area rooted at $y$, and bounded by angles $\alpha$ and $\beta$. The general form of a constraint is a disjunction of the form $[r_1\vee...\vee r_{n_1}\vee (\alpha_1,\beta_1)\vee...\vee (\alpha _{n_2},\beta_{n_2})](x,y)$, with $r_i(x,y)$, $i=1... n_1$, and $(\alpha _i,\beta_i)(x,y)$, $i=1... n_2$, being convex constraints as described above: the meaning of such a general constraint is that, for some $i=1... n_1$, $r_i(x,y)$ holds, or, for some $i=1... n_2$, $(\alpha_i,\beta_i)(x,y)$ holds. A conjunction of such general constraints is a $\tcsp$-like CSP, which we will refer to as an $\scsp$ (Spatial Constraint Satisfaction Problem). An effective solution search algorithm for an $\scsp$ will be described, which uses (1) constraint propagation, based on a composition operation to be defined, as the filtering method during the search, and (2) the Simplex algorithm, guaranteeing completeness, at the leaves of the search tree. The approach is particularly suited for large-scale high-level vision, such as, e.g., satellite-like surveillance of a geographic area.
cs/0311052
A Situation Calculus-based Approach To Model Ubiquitous Information Services
cs.AI cs.HC
This paper presents an augmented situation calculus-based approach to model autonomous computing paradigm in ubiquitous information services. To make it practical for commercial development and easier to support autonomous paradigm imposed by ubiquitous information services, we made improvements based on Reiter's standard situation calculus. First we explore the inherent relationship between fluents and evolution: since not all fluents contribute to systems' evolution and some fluents can be derived from some others, we define those fluents that are sufficient and necessary to determine evolutional potential as decisive fluents, and then we prove that their successor states wrt to deterministic complex actions satisfy Markov property. Then, within the calculus framework we build, we introduce validity theory to model the autonomous services with application-specific validity requirements, including: validity fluents to axiomatize validity requirements, heuristic multiple alternative service choices ranging from complete acceptance, partial acceptance, to complete rejection, and validity-ensured policy to comprise such alternative service choices into organic, autonomously-computable services. Our approach is demonstrated by a ubiquitous calendaring service, ACS, throughout the paper.
cs/0312003
Hybrid LQG-Neural Controller for Inverted Pendulum System
cs.NE cs.LG
The paper presents a hybrid system controller, incorporating a neural and an LQG controller. The neural controller has been optimized by genetic algorithms directly on the inverted pendulum system. The failure free optimization process stipulated a relatively small region of the asymptotic stability of the neural controller, which is concentrated around the regulation point. The presented hybrid controller combines benefits of a genetically optimized neural controller and an LQG controller in a single system controller. High quality of the regulation process is achieved through utilization of the neural controller, while stability of the system during transient processes and a wide range of operation are assured through application of the LQG controller. The hybrid controller has been validated by applying it to a simulation model of an inherently unstable system of inverted pendulum.
cs/0312004
Improving spam filtering by combining Naive Bayes with simple k-nearest neighbor searches
cs.LG
Using naive Bayes for email classification has become very popular within the last few months. They are quite easy to implement and very efficient. In this paper we want to present empirical results of email classification using a combination of naive Bayes and k-nearest neighbor searches. Using this technique we show that the accuracy of a Bayes filter can be improved slightly for a high number of features and significantly for a small number of features.
cs/0312008
Embedding Web-based Statistical Translation Models in Cross-Language Information Retrieval
cs.CL cs.IR
Although more and more language pairs are covered by machine translation services, there are still many pairs that lack translation resources. Cross-language information retrieval (CLIR) is an application which needs translation functionality of a relatively low level of sophistication since current models for information retrieval (IR) are still based on a bag-of-words. The Web provides a vast resource for the automatic construction of parallel corpora which can be used to train statistical translation models automatically. The resulting translation models can be embedded in several ways in a retrieval model. In this paper, we will investigate the problem of automatically mining parallel texts from the Web and different ways of integrating the translation models within the retrieval process. Our experiments on standard test collections for CLIR show that the Web-based translation models can surpass commercial MT systems in CLIR tasks. These results open the perspective of constructing a fully automatic query translation device for CLIR at a very low cost.
cs/0312009
Failure-Free Genetic Algorithm Optimization of a System Controller Using SAFE/LEARNING Controllers in Tandem
cs.NE cs.LG
The paper presents a method for failure free genetic algorithm optimization of a system controller. Genetic algorithms present a powerful tool that facilitates producing near-optimal system controllers. Applied to such methods of computational intelligence as neural networks or fuzzy logic, these methods are capable of combining the non-linear mapping capabilities of the latter with learning the system behavior directly, that is, without a prior model. At the same time, genetic algorithms routinely produce solutions that lead to the failure of the controlled system. Such solutions are generally unacceptable for applications where safe operation must be guaranteed. We present here a method of design, which allows failure-free application of genetic algorithms through utilization of SAFE and LEARNING controllers in tandem, where the SAFE controller recovers the system from dangerous states while the LEARNING controller learns its behavior. The method has been validated by applying it to an inherently unstable system of inverted pendulum.
cs/0312016
Taking the Initiative with Extempore: Exploring Out-of-Turn Interactions with Websites
cs.HC cs.IR
We present the first study to explore the use of out-of-turn interaction in websites. Out-of-turn interaction is a technique which empowers the user to supply unsolicited information while browsing. This approach helps flexibly bridge any mental mismatch between the user and the website, in a manner fundamentally different from faceted browsing and site-specific search tools. We built a user interface (Extempore) which accepts out-of-turn input via voice or text; and employed it in a US congressional website, to determine if users utilize out-of-turn interaction for information-finding tasks, and their rationale for doing so. The results indicate that users are adept at discerning when out-of-turn interaction is necessary in a particular task, and actively interleaved it with browsing. However, users found cascading information across information-finding subtasks challenging. Therefore, this work not only improves our understanding of out-of-turn interaction, but also suggests further opportunities to enrich browsing experiences for users.
cs/0312018
Mapping Subsets of Scholarly Information
cs.IR cs.LG
We illustrate the use of machine learning techniques to analyze, structure, maintain, and evolve a large online corpus of academic literature. An emerging field of research can be identified as part of an existing corpus, permitting the implementation of a more coherent community structure for its practitioners.
cs/0312020
Modeling Object Oriented Constraint Programs in Z
cs.AI
Object oriented constraint programs (OOCPs) emerge as a leading evolution of constraint programming and artificial intelligence, first applied to a range of industrial applications called configuration problems. The rich variety of technical approaches to solving configuration problems (CLP(FD), CC(FD), DCSP, Terminological systems, constraint programs with set variables ...) is a source of difficulty. No universally accepted formal language exists for communicating about OOCPs, which makes the comparison of systems difficult. We present here a Z based specification of OOCPs which avoids the falltrap of hidden object semantics. The object system is part of the specification, and captures all of the most advanced notions from the object oriented modeling standard UML. The paper illustrates these issues and the conciseness and precision of Z by the specification of a working OOCP that solves an historical AI problem : parsing a context free grammar. Being written in Z, an OOCP specification also supports formal proofs. The whole builds the foundation of an adaptative and evolving framework for communicating about constrained object models and programs.
cs/0312024
Evolution: Google vs. DRIS
cs.DL cs.IR cs.NI
This paper gives an absolute new search system that builds the information retrieval infrastructure for Internet. Now most search engine companies are mainly concerned with how to make profit from company users by advertisement and ranking prominence, but never consider what its real customers will feel. Few web search engines can sell billions dollars just at the cost of inconvenience of most Internet users, but not its high quality of search service. When we have to bear the bothersome advertisements in the awful results and have no choices, Internet as the kind of public good will surely be undermined. If current Internet can't fully ensure our right to know, it may need some sound improvements or a revolution.
cs/0312025
Soft Constraint Programming to Analysing Security Protocols
cs.CR cs.AI
Security protocols stipulate how the remote principals of a computer network should interact in order to obtain specific security goals. The crucial goals of confidentiality and authentication may be achieved in various forms, each of different strength. Using soft (rather than crisp) constraints, we develop a uniform formal notion for the two goals. They are no longer formalised as mere yes/no properties as in the existing literature, but gain an extra parameter, the security level. For example, different messages can enjoy different levels of confidentiality, or a principal can achieve different levels of authentication with different principals. The goals are formalised within a general framework for protocol analysis that is amenable to mechanisation by model checking. Following the application of the framework to analysing the asymmetric Needham-Schroeder protocol, we have recently discovered a new attack on that protocol as a form of retaliation by principals who have been attacked previously. Having commented on that attack, we then demonstrate the framework on a bigger, largely deployed protocol consisting of three phases, Kerberos.
cs/0312026
Speedup of Logic Programs by Binarization and Partial Deduction
cs.PL cs.AI
Binary logic programs can be obtained from ordinary logic programs by a binarizing transformation. In most cases, binary programs obtained this way are less efficient than the original programs. (Demoen, 1992) showed an interesting example of a logic program whose computational behaviour was improved when it was transformed to a binary program and then specialized by partial deduction. The class of B-stratifiable logic programs is defined. It is shown that for every B-stratifiable logic program, binarization and subsequent partial deduction produce a binary program which does not contain variables for continuations introduced by binarization. Such programs usually have a better computational behaviour than the original ones. Both binarization and partial deduction can be easily automated. A comparison with other related approaches to program transformation is given.
cs/0312028
Minimal founded semantics for disjunctive logic programs and deductive databases
cs.LO cs.AI
In this paper, we propose a variant of stable model semantics for disjunctive logic programming and deductive databases. The semantics, called minimal founded, generalizes stable model semantics for normal (i.e. non disjunctive) programs but differs from disjunctive stable model semantics (the extension of stable model semantics for disjunctive programs). Compared with disjunctive stable model semantics, minimal founded semantics seems to be more intuitive, it gives meaning to programs which are meaningless under stable model semantics and is no harder to compute. More specifically, minimal founded semantics differs from stable model semantics only for disjunctive programs having constraint rules or rules working as constraints. We study the expressive power of the semantics and show that for general disjunctive datalog programs it has the same power as disjunctive stable model semantics.
cs/0312029
Strong Equivalence Made Easy: Nested Expressions and Weight Constraints
cs.LO cs.AI
Logic programs P and Q are strongly equivalent if, given any program R, programs P union R and Q union R are equivalent (that is, have the same answer sets). Strong equivalence is convenient for the study of equivalent transformations of logic programs: one can prove that a local change is correct without considering the whole program. Lifschitz, Pearce and Valverde showed that Heyting's logic of here-and-there can be used to characterize strong equivalence for logic programs with nested expressions (which subsume the better-known extended disjunctive programs). This note considers a simpler, more direct characterization of strong equivalence for such programs, and shows that it can also be applied without modification to the weight constraint programs of Niemela and Simons. Thus, this characterization of strong equivalence is convenient for the study of equivalent transformations of logic programs written in the input languages of answer set programming systems dlv and smodels. The note concludes with a brief discussion of results that can be used to automate reasoning about strong equivalence, including a novel encoding that reduces the problem of deciding the strong equivalence of a pair of weight constraint programs to that of deciding the inconsistency of a weight constraint program.
cs/0312033
Using sensors in the web crawling process
cs.IR cs.DL
This paper offers a short description of an Internet information field monitoring system, which places a special module-sensor on the side of the Web-server to detect changes in information resources and subsequently reindexes only the resources signalized by the corresponding sensor. Concise results of simulation research and an implementation attempt of the given "sensors" concept are provided.
cs/0312036
What Causes a System to Satisfy a Specification?
cs.LO cs.AI
Even when a system is proven to be correct with respect to a specification, there is still a question of how complete the specification is, and whether it really covers all the behaviors of the system. Coverage metrics attempt to check which parts of a system are actually relevant for the verification process to succeed. Recent work on coverage in model checking suggests several coverage metrics and algorithms for finding parts of the system that are not covered by the specification. The work has already proven to be effective in practice, detecting design errors that escape early verification efforts in industrial settings. In this paper, we relate a formal definition of causality given by Halpern and Pearl [2001] to coverage. We show that it gives significant insight into unresolved issues regarding the definition of coverage and leads to potentially useful extensions of coverage. In particular, we introduce the notion of responsibility, which assigns to components of a system a quantitative measure of their relevance to the satisfaction of the specification.
cs/0312037
Characterizing and Reasoning about Probabilistic and Non-Probabilistic Expectation
cs.AI cs.LO
Expectation is a central notion in probability theory. The notion of expectation also makes sense for other notions of uncertainty. We introduce a propositional logic for reasoning about expectation, where the semantics depends on the underlying representation of uncertainty. We give sound and complete axiomatizations for the logic in the case that the underlying representation is (a) probability, (b) sets of probability measures, (c) belief functions, and (d) possibility measures. We show that this logic is more expressive than the corresponding logic for reasoning about likelihood in the case of sets of probability measures, but equi-expressive in the case of probability, belief, and possibility. Finally, we show that satisfiability for these logics is NP-complete, no harder than satisfiability for propositional logic.
cs/0312038
Responsibility and blame: a structural-model approach
cs.AI cs.LO
Causality is typically treated an all-or-nothing concept; either A is a cause of B or it is not. We extend the definition of causality introduced by Halpern and Pearl [2001] to take into account the degree of responsibility of A for B. For example, if someone wins an election 11--0, then each person who votes for him is less responsible for the victory than if he had won 6--5. We then define a notion of degree of blame, which takes into account an agent's epistemic state. Roughly speaking, the degree of blame of A for B is the expected degree of responsibility of A for B, taken over the epistemic state of an agent.
cs/0312040
Diagnostic reasoning with A-Prolog
cs.AI
In this paper we suggest an architecture for a software agent which operates a physical device and is capable of making observations and of testing and repairing the device's components. We present simplified definitions of the notions of symptom, candidate diagnosis, and diagnosis which are based on the theory of action language ${\cal AL}$. The definitions allow one to give a simple account of the agent's behavior in which many of the agent's tasks are reduced to computing stable models of logic programs.
cs/0312041
Greedy Algorithms in Datalog
cs.DB cs.AI
In the design of algorithms, the greedy paradigm provides a powerful tool for solving efficiently classical computational problems, within the framework of procedural languages. However, expressing these algorithms within the declarative framework of logic-based languages has proven a difficult research challenge. In this paper, we extend the framework of Datalog-like languages to obtain simple declarative formulations for such problems, and propose effective implementation techniques to ensure computational complexities comparable to those of procedural formulations. These advances are achieved through the use of the "choice" construct, extended with preference annotations to effect the selection of alternative stable-models and nondeterministic fixpoints. We show that, with suitable storage structures, the differential fixpoint computation of our programs matches the complexity of procedural algorithms in classical search and optimization problems.
cs/0312042
Declarative Semantics for Active Rules
cs.DB
In this paper we analyze declarative deterministic and non-deterministic semantics for active rules. In particular we consider several (partial) stable model semantics, previously defined for deductive rules, such as well-founded, max deterministic, unique total stable model, total stable model, and maximal stable model semantics. The semantics of an active program AP is given by first rewriting it into a deductive program P, then computing a model M defining the declarative semantics of P and, finally, applying `consistent' updates contained in M to the source database. The framework we propose permits a natural integration of deductive and active rules and can also be applied to queries with function symbols or to queries over infinite databases.
cs/0312043
On A Theory of Probabilistic Deductive Databases
cs.DB
We propose a framework for modeling uncertainty where both belief and doubt can be given independent, first-class status. We adopt probability theory as the mathematical formalism for manipulating uncertainty. An agent can express the uncertainty in her knowledge about a piece of information in the form of a confidence level, consisting of a pair of intervals of probability, one for each of her belief and doubt. The space of confidence levels naturally leads to the notion of a trilattice, similar in spirit to Fitting's bilattices. Intuitively, thep oints in such a trilattice can be ordered according to truth, information, or precision. We develop a framework for probabilistic deductive databases by associating confidence levels with the facts and rules of a classical deductive database. While the trilattice structure offers a variety of choices for defining the semantics of probabilistic deductive databases, our choice of semantics is based on the truth-ordering, which we find to be closest to the classical framework for deductive databases. In addition to proposing a declarative semantics based on valuations and an equivalent semantics based on fixpoint theory, we also propose a proof procedure and prove it sound and complete. We show that while classical Datalog query programs have a polynomial time data complexity, certain query programs in the probabilistic deductive database framework do not even terminate on some input databases. We identify a large natural class of query programs of practical interest in our framework, and show that programs in this class possess polynomial time data complexity, i.e., not only do they terminate on every input database, they are guaranteed to do so in a number of steps polynomial in the input database size.
cs/0312044
Clustering by compression
cs.CV cond-mat.stat-mech cs.AI physics.data-an q-bio.GN q-bio.QM
We present a new method for clustering based on compression. The method doesn't use subject-specific features or background knowledge, and works as follows: First, we determine a universal similarity distance, the normalized compression distance or NCD, computed from the lengths of compressed data files (singly and in pairwise concatenation). Second, we apply a hierarchical clustering method. The NCD is universal in that it is not restricted to a specific application area, and works across application area boundaries. A theoretical precursor, the normalized information distance, co-developed by one of the authors, is provably optimal but uses the non-computable notion of Kolmogorov complexity. We propose precise notions of similarity metric, normal compressor, and show that the NCD based on a normal compressor is a similarity metric that approximates universality. To extract a hierarchy of clusters from the distance matrix, we determine a dendrogram (binary tree) by a new quartet method and a fast heuristic to implement it. The method is implemented and available as public software, and is robust under choice of different compressors. To substantiate our claims of universality and robustness, we report evidence of successful application in areas as diverse as genomics, virology, languages, literature, music, handwritten digits, astronomy, and combinations of objects from completely different domains, using statistical, dictionary, and block sorting compressors. In genomics we presented new evidence for major questions in Mammalian evolution, based on whole-mitochondrial genomic analysis: the Eutherian orders and the Marsupionta hypothesis against the Theria hypothesis.
cs/0312045
Weight Constraints as Nested Expressions
cs.AI
We compare two recent extensions of the answer set (stable model) semantics of logic programs. One of them, due to Lifschitz, Tang and Turner, allows the bodies and heads of rules to contain nested expressions. The other, due to Niemela and Simons, uses weight constraints. We show that there is a simple, modular translation from the language of weight constraints into the language of nested expressions that preserves the program's answer sets. Nested expressions can be eliminated from the result of this translation in favor of additional atoms. The translation makes it possible to compute answer sets for some programs with weight constraints using satisfiability solvers, and to prove the strong equivalence of programs with weight constraints using the logic of here-and there.
cs/0312046
On the Abductive or Deductive Nature of Database Schema Validation and Update Processing Problems
cs.DB cs.LO
We show that database schema validation and update processing problems such as view updating, materialized view maintenance, integrity constraint checking, integrity constraint maintenance or condition monitoring can be classified as problems of either abductive or deductive nature, according to the reasoning paradigm that inherently suites them. This is done by performing abductive and deductive reasoning on the event rules [Oli91], a set of rules that define the difference between consecutive database states In this way, we show that it is possible to provide methods able to deal with all these problems as a whole. We also show how some existing general deductive and abductive procedures may be used to reason on the event rules. In this way, we show that these procedures can deal with all database schema validation and update processing problems considered in this paper.
cs/0312047
Mapping weblog communities
cs.NE
Websites of a particular class form increasingly complex networks, and new tools are needed to map and understand them. A way of visualizing this complex network is by mapping it. A map highlights which members of the community have similar interests, and reveals the underlying social network. In this paper, we will map a network of websites using Kohonen's self-organizing map (SOM), a neural-net like method generally used for clustering and visualization of complex data sets. The set of websites considered has been the Blogalia weblog hosting site (based at http://www.blogalia.com/), a thriving community of around 200 members, created in January 2002. In this paper we show how SOM discovers interesting community features, its relation with other community-discovering algorithms, and the way it highlights the set of communities formed over the network.
cs/0312048
Representation Dependence in Probabilistic Inference
cs.AI cs.LO
Non-deductive reasoning systems are often {\em representation dependent}: representing the same situation in two different ways may cause such a system to return two different answers. Some have viewed this as a significant problem. For example, the principle of maximum entropy has been subjected to much criticism due to its representation dependence. There has, however, been almost no work investigating representation dependence. In this paper, we formalize this notion and show that it is not a problem specific to maximum entropy. In fact, we show that any representation-independent probabilistic inference procedure that ignores irrelevant information is essentially entailment, in a precise sense. Moreover, we show that representation independence is incompatible with even a weak default assumption of independence. We then show that invariance under a restricted class of representation changes can form a reasonable compromise between representation independence and other desiderata, and provide a construction of a family of inference procedures that provides such restricted representation independence, using relative entropy.
cs/0312050
A Flexible Pragmatics-driven Language Generator for Animated Agents
cs.CL cs.MM
This paper describes the NECA MNLG; a fully implemented Multimodal Natural Language Generation module. The MNLG is deployed as part of the NECA system which generates dialogues between animated agents. The generation module supports the seamless integration of full grammar rules, templates and canned text. The generator takes input which allows for the specification of syntactic, semantic and pragmatic constraints on the output.
cs/0312051
Towards Automated Generation of Scripted Dialogue: Some Time-Honoured Strategies
cs.CL cs.AI
The main aim of this paper is to introduce automated generation of scripted dialogue as a worthwhile topic of investigation. In particular the fact that scripted dialogue involves two layers of communication, i.e., uni-directional communication between the author and the audience of a scripted dialogue and bi-directional pretended communication between the characters featuring in the dialogue, is argued to raise some interesting issues. Our hope is that the combined study of the two layers will forge links between research in text generation and dialogue processing. The paper presents a first attempt at creating such links by studying three types of strategies for the automated generation of scripted dialogue. The strategies are derived from examples of human-authored and naturally occurring dialogue.
cs/0312052
Dialogue as Discourse: Controlling Global Properties of Scripted Dialogue
cs.CL cs.AI
This paper explains why scripted dialogue shares some crucial properties with discourse. In particular, when scripted dialogues are generated by a Natural Language Generation system, the generator can apply revision strategies that cannot normally be used when the dialogue results from an interaction between autonomous agents (i.e., when the dialogue is not scripted). The paper explains that the relevant revision operators are best applied at the level of a dialogue plan and discusses how the generator may decide when to apply a given revision operator.
cs/0312053
On the Expressibility of Stable Logic Programming
cs.AI
(We apologize for pidgin LaTeX) Schlipf \cite{sch91} proved that Stable Logic Programming (SLP) solves all $\mathit{NP}$ decision problems. We extend Schlipf's result to prove that SLP solves all search problems in the class $\mathit{NP}$. Moreover, we do this in a uniform way as defined in \cite{mt99}. Specifically, we show that there is a single $\mathrm{DATALOG}^{\neg}$ program $P_{\mathit{Trg}}$ such that given any Turing machine $M$, any polynomial $p$ with non-negative integer coefficients and any input $\sigma$ of size $n$ over a fixed alphabet $\Sigma$, there is an extensional database $\mathit{edb}_{M,p,\sigma}$ such that there is a one-to-one correspondence between the stable models of $\mathit{edb}_{M,p,\sigma} \cup P_{\mathit{Trg}}$ and the accepting computations of the machine $M$ that reach the final state in at most $p(n)$ steps. Moreover, $\mathit{edb}_{M,p,\sigma}$ can be computed in polynomial time from $p$, $\sigma$ and the description of $M$ and the decoding of such accepting computations from its corresponding stable model of $\mathit{edb}_{M,p,\sigma} \cup P_{\mathit{Trg}}$ can be computed in linear time. A similar statement holds for Default Logic with respect to $\Sigma_2^\mathrm{P}$-search problems\footnote{The proof of this result involves additional technical complications and will be a subject of another publication.}.
cs/0312057
Abduction in Well-Founded Semantics and Generalized Stable Models
cs.LO cs.AI
Abductive logic programming offers a formalism to declaratively express and solve problems in areas such as diagnosis, planning, belief revision and hypothetical reasoning. Tabled logic programming offers a computational mechanism that provides a level of declarativity superior to that of Prolog, and which has supported successful applications in fields such as parsing, program analysis, and model checking. In this paper we show how to use tabled logic programming to evaluate queries to abductive frameworks with integrity constraints when these frameworks contain both default and explicit negation. The result is the ability to compute abduction over well-founded semantics with explicit negation and answer sets. Our approach consists of a transformation and an evaluation method. The transformation adjoins to each objective literal $O$ in a program, an objective literal $not(O)$ along with rules that ensure that $not(O)$ will be true if and only if $O$ is false. We call the resulting program a {\em dual} program. The evaluation method, \wfsmeth, then operates on the dual program. \wfsmeth{} is sound and complete for evaluating queries to abductive frameworks whose entailment method is based on either the well-founded semantics with explicit negation, or on answer sets. Further, \wfsmeth{} is asymptotically as efficient as any known method for either class of problems. In addition, when abduction is not desired, \wfsmeth{} operating on a dual program provides a novel tabling method for evaluating queries to ground extended programs whose complexity and termination properties are similar to those of the best tabling methods for the well-founded semantics. A publicly available meta-interpreter has been developed for \wfsmeth{} using the XSB system.
cs/0312058
Acquiring Lexical Paraphrases from a Single Corpus
cs.CL cs.AI cs.IR cs.LG
This paper studies the potential of identifying lexical paraphrases within a single corpus, focusing on the extraction of verb paraphrases. Most previous approaches detect individual paraphrase instances within a pair (or set) of comparable corpora, each of them containing roughly the same information, and rely on the substantial level of correspondence of such corpora. We present a novel method that successfully detects isolated paraphrase instances within a single corpus without relying on any a-priori structure and information. A comparison suggests that an instance-based approach may be combined with a vector based approach in order to assess better the paraphrase likelihood for many verb pairs.
cs/0312059
Polyhierarchical Classifications Induced by Criteria Polyhierarchies, and Taxonomy Algebra
cs.AI cs.IR
A new approach to the construction of general persistent polyhierarchical classifications is proposed. It is based on implicit description of category polyhierarchy by a generating polyhierarchy of classification criteria. Similarly to existing approaches, the classification categories are defined by logical functions encoded by attributive expressions. However, the generating hierarchy explicitly predefines domains of criteria applicability, and the semantics of relations between categories is invariant to changes in the universe composition, extending variety of criteria, and increasing their cardinalities. The generating polyhierarchy is an independent, compact, portable, and re-usable information structure serving as a template classification. It can be associated with one or more particular sets of objects, included in more general classifications as a standard component, or used as a prototype for more comprehensive classifications. The approach dramatically simplifies development and unplanned modifications of persistent hierarchical classifications compared with tree, DAG, and faceted schemes. It can be efficiently implemented in common DBMS, while considerably reducing amount of computer resources required for storage, maintenance, and use of complex polyhierarchies.
cs/0312060
Part-of-Speech Tagging with Minimal Lexicalization
cs.CL cs.LG
We use a Dynamic Bayesian Network to represent compactly a variety of sublexical and contextual features relevant to Part-of-Speech (PoS) tagging. The outcome is a flexible tagger (LegoTag) with state-of-the-art performance (3.6% error on a benchmark corpus). We explore the effect of eliminating redundancy and radically reducing the size of feature vocabularies. We find that a small but linguistically motivated set of suffixes results in improved cross-corpora generalization. We also show that a minimal lexicon limited to function words is sufficient to ensure reasonable performance.
cs/0401004
Cyborg Systems as Platforms for Computer-Vision Algorithm-Development for Astrobiology
cs.CV astro-ph cs.AI
Employing the allegorical imagery from the film "The Matrix", we motivate and discuss our `Cyborg Astrobiologist' research program. In this research program, we are using a wearable computer and video camcorder in order to test and train a computer-vision system to be a field-geologist and field-astrobiologist.
cs/0401005
About Unitary Rating Score Constructing
cs.LG
It is offered to pool test points of different subjects and different aspects of the same subject together in order to get the unitary rating score, by the way of nonlinear transformation of indicator points in accordance with Zipf's distribution. It is proposed to use the well-studied distribution of Intellectuality Quotient IQ as the reference distribution for latent variable "progress in studies".
cs/0401009
Unifying Computing and Cognition: The SP Theory and its Applications
cs.AI
This book develops the conjecture that all kinds of information processing in computers and in brains may usefully be understood as "information compression by multiple alignment, unification and search". This "SP theory", which has been under development since 1987, provides a unified view of such things as the workings of a universal Turing machine, the nature of 'knowledge', the interpretation and production of natural language, pattern recognition and best-match information retrieval, several kinds of probabilistic reasoning, planning and problem solving, unsupervised learning, and a range of concepts in mathematics and logic. The theory also provides a basis for the design of an 'SP' computer with several potential advantages compared with traditional digital computers.
cs/0401014
Nested Intervals with Farey Fractions
cs.DB
Relational Databases are universally conceived as an advance over their predecessors Network and Hierarchical models. Superior in every querying respect, they turned out to be surprisingly incomplete when modeling transitive dependencies. Almost every couple of months a question how to model a tree in the database surfaces at comp.database.theory newsgroup. This article completes a series of articles exploring Nested Intervals Model. Previous articles introduced tree encoding with Binary Rational Numbers. However, binary encoding grows exponentially, both in breadth and in depth. In this article, we'll leverage Farey fractions in order to overcome this problem. We'll also demonstrate that our implementation scales to a tree with 1M nodes.
cs/0401015
Query Answering in Peer-to-Peer Data Exchange Systems
cs.DB cs.LO
The problem of answering queries posed to a peer who is a member of a peer-to-peer data exchange system is studied. The answers have to be consistent wrt to both the local semantic constraints and the data exchange constraints with other peers; and must also respect certain trust relationships between peers. A semantics for peer consistent answers under exchange constraints and trust relationships is introduced and some techniques for obtaining those answers are presented.
cs/0401017
Better Foreground Segmentation Through Graph Cuts
cs.CV
For many tracking and surveillance applications, background subtraction provides an effective means of segmenting objects moving in front of a static background. Researchers have traditionally used combinations of morphological operations to remove the noise inherent in the background-subtracted result. Such techniques can effectively isolate foreground objects, but tend to lose fidelity around the borders of the segmentation, especially for noisy input. This paper explores the use of a minimum graph cut algorithm to segment the foreground, resulting in qualitatively and quantitiatively cleaner segmentations. Experiments on both artificial and real data show that the graph-based method reduces the error around segmented foreground objects. A MATLAB code implementation is available at http://www.cs.smith.edu/~nhowe/research/code/#fgseg
cs/0401018
Factor Temporal Prognosis of Tick-Borne Encephalitis Foci Functioning on the South of Russian Far East
cs.CV
A method of temporal factor prognosis of TE (tick-borne encephalitis) infection has been developed. The high precision of the prognosis results for a number of geographical regions of Primorsky Krai has been achieved. The method can be applied not only to epidemiological research but also to others.
cs/0401020
Presynaptic modulation as fast synaptic switching: state-dependent modulation of task performance
cs.NE q-bio.NC
Neuromodulatory receptors in presynaptic position have the ability to suppress synaptic transmission for seconds to minutes when fully engaged. This effectively alters the synaptic strength of a connection. Much work on neuromodulation has rested on the assumption that these effects are uniform at every neuron. However, there is considerable evidence to suggest that presynaptic regulation may be in effect synapse-specific. This would define a second "weight modulation" matrix, which reflects presynaptic receptor efficacy at a given site. Here we explore functional consequences of this hypothesis. By analyzing and comparing the weight matrices of networks trained on different aspects of a task, we identify the potential for a low complexity "modulation matrix", which allows to switch between differently trained subtasks while retaining general performance characteristics for the task. This means that a given network can adapt itself to different task demands by regulating its release of neuromodulators. Specifically, we suggest that (a) a network can provide optimized responses for related classification tasks without the need to train entirely separate networks and (b) a network can blend a "memory mode" which aims at reproducing memorized patterns and a "novelty mode" which aims to facilitate classification of new patterns. We relate this work to the known effects of neuromodulators on brain-state dependent processing.
cs/0401025
Running C++ models undet the Swarm environment
cs.MA
Objective-C is still the language of choice if users want to run their simulation efficiently under the Swarm environment since the Swarm environment itself was written in Objective-C. The language is a fast, object-oriented and easy to learn. However, the language is less well known than, less expressive than, and lacks support for many important features of C++ (eg. OpenMP for high performance computing application). In this paper, we present a methodology and software tools that we have developed for auto generating an Objective-C object template (and all the necessary interfacing functions) from a given C++ model, utilising the Classdesc's object description technology, so that the C++ model can both be run and accessed under the Objective-C and C++ environments. We also present a methodology for modifying an existing Swarm application to make part of the model (eg. the heatbug's step method) run under the C++ environment.
cs/0401026
EcoLab: Agent Based Modeling for C++ programmers
cs.MA
\EcoLab{} is an agent based modeling system for C++ programmers, strongly influenced by the design of Swarm. This paper is just a brief outline of \EcoLab's features, more details can be found in other published articles, documentation and source code from the \EcoLab{} website.
cs/0402001
Mobile Re-Finding of Web Information Using a Voice Interface
cs.HC cs.IR
Mobile access to information is a considerable problem for many users, especially to information found on the Web. In this paper, we explore how a voice-controlled service, accessible by telephone, could support mobile users' needs for refinding specific information previously found on the Web. We outline challenges in creating such a service and describe architectural and user interfaces issues discovered in an exploratory prototype we built called WebContext. We also present the results of a study, motivated by our experience with WebContext, to explore what people remember about information that they are trying to refind and how they express information refinding requests in a collaborative conversation. As part of the study, we examine how end-usercreated Web page annotations can be used to help support mobile information re-finding. We observed the use of URLs, page titles, and descriptions of page contents to help identify waypoints in the search process. Furthermore, we observed that the annotations were utilized extensively, indicating that explicitly added context by the user can play an important role in re-finding.
cs/0402003
Semantic Optimization of Preference Queries
cs.DB
The notion of preference is becoming more and more ubiquitous in present-day information systems. Preferences are primarily used to filter and personalize the information reaching the users of such systems. In database systems, preferences are usually captured as preference relations that are used to build preference queries. In our approach, preference queries are relational algebra or SQL queries that contain occurrences of the winnow operator ("find the most preferred tuples in a given relation"). We present here a number of semantic optimization techniques applicable to preference queries. The techniques make use of integrity constraints, and make it possible to remove redundant occurrences of the winnow operator and to apply a more efficient algorithm for the computation of winnow. We also study the propagation of integrity constraints in the result of the winnow. We have identified necessary and sufficient conditions for the applicability of our techniques, and formulated those conditions as constraint satisfiability problems.
cs/0402007
An Integrated Approach for Extraction of Objects from XML and Transformation to Heterogeneous Object Oriented Databases
cs.DB cs.SE
CERN's (European Organization for Nuclear Research) WISDOM project uses XML for the replication of data between different data repositories in a heterogeneous operating system environment. For exchanging data from Web-resident databases, the data needs to be transformed into XML and back to the database format. Many different approaches are employed to do this transformation. This paper addresses issues that make this job more efficient and robust than existing approaches. It incorporates the World Wide Web Consortium (W3C) XML Schema specification in the database-XML relationship. Incorporation of the XML Schema exhibits significant improvements in XML content usage and reduces the limitations of DTD-based database XML services. Secondly the paper explores the possibility of database independent transformation of data between XML and different databases. It proposes a standard XML format that every serialized object should follow. This makes it possible to use objects of heterogeneous database seamlessly using XML.
cs/0402008
A Use-Case Driven Approach in Requirements Engineering : The Mammogrid Project
cs.DB cs.SE
We report on the application of the use-case modeling technique to identify and specify the user requirements of the MammoGrid project in an incremental and controlled iterative approach. Modeling has been carried out in close collaboration with clinicians and radiologists with no prior experience of use cases. The study reveals the advantages and limitations of applying this technique to requirements specification in the domains of breast cancer screening and mammography research, with implications for medical imaging more generally. In addition, this research has shown a return on investment in use-case modeling in shorter gaps between phases of the requirements engineering process. The qualitative result of this analysis leads us to propose that a use-case modeling approach may result in reducing the cycle of the requirements engineering process for medical imaging.
cs/0402009
Resolving Clinicians Queries Across a Grids Infrastructure
cs.DB cs.SE
The past decade has witnessed order of magnitude increases in computing power, data storage capacity and network speed, giving birth to applications which may handle large data volumes of increased complexity, distributed over the Internet. Grids computing promises to resolve many of the difficulties in facilitating medical image analysis to allow radiologists to collaborate without having to co-locate. The EU-funded MammoGrid project aims to investigate the feasibility of developing a Grid-enabled European database of mammograms and provide an information infrastructure which federates multiple mammogram databases. This will enable clinicians to develop new common, collaborative and co-operative approaches to the analysis of mammographic data. This paper focuses on one of the key requirements for large-scale distributed mammogram analysis: resolving queries across a grid-connected federation of images.
cs/0402013
Corollaries on the fixpoint completion: studying the stable semantics by means of the Clark completion
cs.AI cs.LO
The fixpoint completion fix(P) of a normal logic program P is a program transformation such that the stable models of P are exactly the models of the Clark completion of fix(P). This is well-known and was studied by Dung and Kanchanasut (1989). The correspondence, however, goes much further: The Gelfond-Lifschitz operator of P coincides with the immediate consequence operator of fix(P), as shown by Wendt (2002), and even carries over to standard operators used for characterizing the well-founded and the Kripke-Kleene semantics. We will apply this knowledge to the study of the stable semantics, and this will allow us to almost effortlessly derive new results concerning fixed-point and metric-based semantics, and neural-symbolic integration.
cs/0402014
Self-Organising Networks for Classification: developing Applications to Science Analysis for Astroparticle Physics
cs.NE astro-ph cs.AI
Physics analysis in astroparticle experiments requires the capability of recognizing new phenomena; in order to establish what is new, it is important to develop tools for automatic classification, able to compare the final result with data from different detectors. A typical example is the problem of Gamma Ray Burst detection, classification, and possible association to known sources: for this task physicists will need in the next years tools to associate data from optical databases, from satellite experiments (EGRET, GLAST), and from Cherenkov telescopes (MAGIC, HESS, CANGAROO, VERITAS).
cs/0402016
Perspects in astrophysical databases
cs.DB astro-ph
Astrophysics has become a domain extremely rich of scientific data. Data mining tools are needed for information extraction from such large datasets. This asks for an approach to data management emphasizing the efficiency and simplicity of data access; efficiency is obtained using multidimensional access methods and simplicity is achieved by properly handling metadata. Moreover, clustering and classification techniques on large datasets pose additional requirements in terms of computation and memory scalability and interpretability of results. In this study we review some possible solutions.
cs/0402019
The Munich Rent Advisor: A Success for Logic Programming on the Internet
cs.AI cs.DS
Most cities in Germany regularly publish a booklet called the {\em Mietspiegel}. It basically contains a verbal description of an expert system. It allows the calculation of the estimated fair rent for a flat. By hand, one may need a weekend to do so. With our computerized version, the {\em Munich Rent Advisor}, the user just fills in a form in a few minutes and the rent is calculated immediately. We also extended the functionality and applicability of the {\em Mietspiegel} so that the user need not answer all questions on the form. The key to computing with partial information using high-level programming was to use constraint logic programming. We rely on the internet, and more specifically the World Wide Web, to provide this service to a broad user group. More than ten thousand people have used our service in the last three years. This article describes the experiences in implementing and using the {\em Munich Rent Advisor}. Our results suggests that logic programming with constraints can be an important ingredient in intelligent internet systems.
cs/0402020
Geometrical Complexity of Classification Problems
cs.CV
Despite encouraging recent progresses in ensemble approaches, classification methods seem to have reached a plateau in development. Further advances depend on a better understanding of geometrical and topological characteristics of point sets in high-dimensional spaces, the preservation of such characteristics under feature transformations and sampling processes, and their interaction with geometrical models used in classifiers. We discuss an attempt to measure such properties from data sets and relate them to classifier accuracies.