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cs/0008033
Temporal Expressions in Japanese-to-English Machine Translation
cs.CL
This paper describes in outline a method for translating Japanese temporal expressions into English. We argue that temporal expressions form a special subset of language that is best handled as a special module in machine translation. The paper deals with problems of lexical idiosyncrasy as well as the choice of arti...
cs/0008034
Lexicalized Stochastic Modeling of Constraint-Based Grammars using Log-Linear Measures and EM Training
cs.CL
We present a new approach to stochastic modeling of constraint-based grammars that is based on log-linear models and uses EM for estimation from unannotated data. The techniques are applied to an LFG grammar for German. Evaluation on an exact match task yields 86% precision for an ambiguity rate of 5.4, and 90% preci...
cs/0008035
Using a Probabilistic Class-Based Lexicon for Lexical Ambiguity Resolution
cs.CL
This paper presents the use of probabilistic class-based lexica for disambiguation in target-word selection. Our method employs minimal but precise contextual information for disambiguation. That is, only information provided by the target-verb, enriched by the condensed information of a probabilistic class-based lex...
cs/0008036
Probabilistic Constraint Logic Programming. Formal Foundations of Quantitative and Statistical Inference in Constraint-Based Natural Language Processing
cs.CL
In this thesis, we present two approaches to a rigorous mathematical and algorithmic foundation of quantitative and statistical inference in constraint-based natural language processing. The first approach, called quantitative constraint logic programming, is conceptualized in a clear logical framework, and presents ...
cs/0009001
Complexity analysis for algorithmically simple strings
cs.LG
Given a reference computer, Kolmogorov complexity is a well defined function on all binary strings. In the standard approach, however, only the asymptotic properties of such functions are considered because they do not depend on the reference computer. We argue that this approach can be more useful if it is refined t...
cs/0009003
Automatic Extraction of Subcategorization Frames for Czech
cs.CL
We present some novel machine learning techniques for the identification of subcategorization information for verbs in Czech. We compare three different statistical techniques applied to this problem. We show how the learning algorithm can be used to discover previously unknown subcategorization frames from the Czech...
cs/0009005
Fast Approximation of Centrality
cs.DS cond-mat.dis-nn cs.SI
Social studies researchers use graphs to model group activities in social networks. An important property in this context is the centrality of a vertex: the inverse of the average distance to each other vertex. We describe a randomized approximation algorithm for centrality in weighted graphs. For graphs exhibiting t...
cs/0009007
Robust Classification for Imprecise Environments
cs.LG
In real-world environments it usually is difficult to specify target operating conditions precisely, for example, target misclassification costs. This uncertainty makes building robust classification systems problematic. We show that it is possible to build a hybrid classifier that will perform at least as well as th...
cs/0009008
Introduction to the CoNLL-2000 Shared Task: Chunking
cs.CL
We describe the CoNLL-2000 shared task: dividing text into syntactically related non-overlapping groups of words, so-called text chunking. We give background information on the data sets, present a general overview of the systems that have taken part in the shared task and briefly discuss their performance.
cs/0009009
Learning to Filter Spam E-Mail: A Comparison of a Naive Bayesian and a Memory-Based Approach
cs.CL cs.IR cs.LG
We investigate the performance of two machine learning algorithms in the context of anti-spam filtering. The increasing volume of unsolicited bulk e-mail (spam) has generated a need for reliable anti-spam filters. Filters of this type have so far been based mostly on keyword patterns that are constructed by hand and ...
cs/0009011
Anaphora Resolution in Japanese Sentences Using Surface Expressions and Examples
cs.CL
Anaphora resolution is one of the major problems in natural language processing. It is also one of the important tasks in machine translation and man/machine dialogue. We solve the problem by using surface expressions and examples. Surface expressions are the words in sentences which provide clues for anaphora resolu...
cs/0009012
Modeling Ambiguity in a Multi-Agent System
cs.CL cs.AI cs.MA
This paper investigates the formal pragmatics of ambiguous expressions by modeling ambiguity in a multi-agent system. Such a framework allows us to give a more refined notion of the kind of information that is conveyed by ambiguous expressions. We analyze how ambiguity affects the knowledge of the dialog participants...
cs/0009014
Combining Linguistic and Spatial Information for Document Analysis
cs.CL cs.DL
We present a framework to analyze color documents of complex layout. In addition, no assumption is made on the layout. Our framework combines in a content-driven bottom-up approach two different sources of information: textual and spatial. To analyze the text, shallow natural language processing tools, such as tagger...
cs/0009015
A Tableaux Calculus for Ambiguous Quantification
cs.CL
Coping with ambiguity has recently received a lot of attention in natural language processing. Most work focuses on the semantic representation of ambiguous expressions. In this paper we complement this work in two ways. First, we provide an entailment relation for a language with ambiguous expressions. Second, we gi...
cs/0009016
Contextual Inference in Computational Semantics
cs.CL cs.AI
In this paper, an application of automated theorem proving techniques to computational semantics is considered. In order to compute the presuppositions of a natural language discourse, several inference tasks arise. Instead of treating these inferences independently of each other, we show how integrating techniques f...
cs/0009017
A Tableau Calculus for Pronoun Resolution
cs.CL cs.AI
We present a tableau calculus for reasoning in fragments of natural language. We focus on the problem of pronoun resolution and the way in which it complicates automated theorem proving for natural language processing. A method for explicitly manipulating contextual information during deduction is proposed, where pro...
cs/0009018
A Resolution Calculus for Dynamic Semantics
cs.CL cs.AI
This paper applies resolution theorem proving to natural language semantics. The aim is to circumvent the computational complexity triggered by natural language ambiguities like pronoun binding, by interleaving pronoun binding with resolution deduction. Therefore disambiguation is only applied to expression that actu...
cs/0009019
Computing Presuppositions by Contextual Reasoning
cs.AI cs.CL
This paper describes how automated deduction methods for natural language processing can be applied more efficiently by encoding context in a more elaborate way. Our work is based on formal approaches to context, and we provide a tableau calculus for contextual reasoning. This is explained by considering an example f...
cs/0009022
A Comparison between Supervised Learning Algorithms for Word Sense Disambiguation
cs.CL cs.AI
This paper describes a set of comparative experiments, including cross-corpus evaluation, between five alternative algorithms for supervised Word Sense Disambiguation (WSD), namely Naive Bayes, Exemplar-based learning, SNoW, Decision Lists, and Boosting. Two main conclusions can be drawn: 1) The LazyBoosting algorith...
cs/0009025
Parsing with the Shortest Derivation
cs.CL
Common wisdom has it that the bias of stochastic grammars in favor of shorter derivations of a sentence is harmful and should be redressed. We show that the common wisdom is wrong for stochastic grammars that use elementary trees instead of context-free rules, such as Stochastic Tree-Substitution Grammars used by Dat...
cs/0009026
An improved parser for data-oriented lexical-functional analysis
cs.CL
We present an LFG-DOP parser which uses fragments from LFG-annotated sentences to parse new sentences. Experiments with the Verbmobil and Homecentre corpora show that (1) Viterbi n best search performs about 100 times faster than Monte Carlo search while both achieve the same accuracy; (2) the DOP hypothesis which st...
cs/0009027
A Classification Approach to Word Prediction
cs.CL cs.AI cs.LG
The eventual goal of a language model is to accurately predict the value of a missing word given its context. We present an approach to word prediction that is based on learning a representation for each word as a function of words and linguistics predicates in its context. This approach raises a few new questions th...
cs/0010001
Design of an Electro-Hydraulic System Using Neuro-Fuzzy Techniques
cs.RO cs.LG
Increasing demands in performance and quality make drive systems fundamental parts in the progressive automation of industrial processes. Their conventional models become inappropriate and have limited scope if one requires a precise and fast performance. So, it is important to incorporate learning capabilities into ...
cs/0010002
Noise Effects in Fuzzy Modelling Systems
cs.NE cs.LG
Noise is source of ambiguity for fuzzy systems. Although being an important aspect, the effects of noise in fuzzy modeling have been little investigated. This paper presents a set of tests using three well-known fuzzy modeling algorithms. These evaluate perturbations in the extracted rule-bases caused by noise pollut...
cs/0010003
Torque Ripple Minimization in a Switched Reluctance Drive by Neuro-Fuzzy Compensation
cs.RO cs.LG
Simple power electronic drive circuit and fault tolerance of converter are specific advantages of SRM drives, but excessive torque ripple has limited its use to special applications. It is well known that controlling the current shape adequately can minimize the torque ripple. This paper presents a new method for sha...
cs/0010004
A Fuzzy Relational Identification Algorithm and Its Application to Predict The Behaviour of a Motor Drive System
cs.RO cs.LG
Fuzzy relational identification builds a relational model describing systems behaviour by a nonlinear mapping between its variables. In this paper, we propose a new fuzzy relational algorithm based on simplified max-min relational equation. The algorithm presents an adaptation method applied to gravity-center of each...
cs/0010006
Applications of Data Mining to Electronic Commerce
cs.LG cs.DB
Electronic commerce is emerging as the killer domain for data mining technology. The following are five desiderata for success. Seldom are they they all present in one data mining application. 1. Data with rich descriptions. For example, wide customer records with many potentially useful fields allow data mining ...
cs/0010010
Fault Detection using Immune-Based Systems and Formal Language Algorithms
cs.CE cs.LG
This paper describes two approaches for fault detection: an immune-based mechanism and a formal language algorithm. The first one is based on the feature of immune systems in distinguish any foreign cell from the body own cell. The formal language approach assumes the system as a linguistic source capable of generati...
cs/0010012
Finding consensus in speech recognition: word error minimization and other applications of confusion networks
cs.CL
We describe a new framework for distilling information from word lattices to improve the accuracy of speech recognition and obtain a more perspicuous representation of a set of alternative hypotheses. In the standard MAP decoding approach the recognizer outputs the string of words corresponding to the path with the h...
cs/0010013
A Public-key based Information Management Model for Mobile Agents
cs.CR cs.DC cs.IR cs.NI
Mobile code based computing requires development of protection schemes that allow digital signature and encryption of data collected by the agents in untrusted hosts. These algorithms could not rely on carrying encryption keys if these keys could be stolen or used to counterfeit data by hostile hosts and agents. As a...
cs/0010014
On a cepstrum-based speech detector robust to white noise
cs.CL cs.CV cs.HC
We study effects of additive white noise on the cepstral representation of speech signals. Distribution of each individual cepstrum coefficient of speech is shown to depend strongly on noise and to overlap significantly with the cepstrum distribution of noise. Based on these studies, we suggest a scalar quantity, V, ...
cs/0010020
Using existing systems to supplement small amounts of annotated grammatical relations training data
cs.CL
Grammatical relationships (GRs) form an important level of natural language processing, but different sets of GRs are useful for different purposes. Therefore, one may often only have time to obtain a small training corpus with the desired GR annotations. To boost the performance from using such a small training corp...
cs/0010021
Towards Understanding the Predictability of Stock Markets from the Perspective of Computational Complexity
cs.CE cs.CC
This paper initiates a study into the century-old issue of market predictability from the perspective of computational complexity. We develop a simple agent-based model for a stock market where the agents are traders equipped with simple trading strategies, and their trades together determine the stock prices. Comput...
cs/0010022
Noise-Tolerant Learning, the Parity Problem, and the Statistical Query Model
cs.LG cs.AI cs.DS
We describe a slightly sub-exponential time algorithm for learning parity functions in the presence of random classification noise. This results in a polynomial-time algorithm for the case of parity functions that depend on only the first O(log n log log n) bits of input. This is the first known instance of an effici...
cs/0010023
Oracle Complexity and Nontransitivity in Pattern Recognition
cs.CC cs.AI cs.CV cs.DS
Different mathematical models of recognition processes are known. In the present paper we consider a pattern recognition algorithm as an oracle computation on a Turing machine. Such point of view seems to be useful in pattern recognition as well as in recursion theory. Use of recursion theory in pattern recognition s...
cs/0010024
Exploring automatic word sense disambiguation with decision lists and the Web
cs.CL
The most effective paradigm for word sense disambiguation, supervised learning, seems to be stuck because of the knowledge acquisition bottleneck. In this paper we take an in-depth study of the performance of decision lists on two publicly available corpora and an additional corpus automatically acquired from the Web...
cs/0010025
Extraction of semantic relations from a Basque monolingual dictionary using Constraint Grammar
cs.CL
This paper deals with the exploitation of dictionaries for the semi-automatic construction of lexicons and lexical knowledge bases. The final goal of our research is to enrich the Basque Lexical Database with semantic information such as senses, definitions, semantic relations, etc., extracted from a Basque monolingu...
cs/0010026
Enriching very large ontologies using the WWW
cs.CL
This paper explores the possibility to exploit text on the world wide web in order to enrich the concepts in existing ontologies. First, a method to retrieve documents from the WWW related to a concept is described. These document collections are used 1) to construct topic signatures (lists of topically related words...
cs/0010027
One Sense per Collocation and Genre/Topic Variations
cs.CL
This paper revisits the one sense per collocation hypothesis using fine-grained sense distinctions and two different corpora. We show that the hypothesis is weaker for fine-grained sense distinctions (70% vs. 99% reported earlier on 2-way ambiguities). We also show that one sense per collocation does hold across corp...
cs/0010030
Reduction of Intermediate Alphabets in Finite-State Transducer Cascades
cs.CL
This article describes an algorithm for reducing the intermediate alphabets in cascades of finite-state transducers (FSTs). Although the method modifies the component FSTs, there is no change in the overall relation described by the whole cascade. No additional information or special algorithm, that could decelerate ...
cs/0010031
Opportunity Cost Algorithms for Combinatorial Auctions
cs.CE cs.DS
Two general algorithms based on opportunity costs are given for approximating a revenue-maximizing set of bids an auctioneer should accept, in a combinatorial auction in which each bidder offers a price for some subset of the available goods and the auctioneer can only accept non-intersecting bids. Since this problem...
cs/0010032
Super Logic Programs
cs.AI cs.LO
The Autoepistemic Logic of Knowledge and Belief (AELB) is a powerful nonmonotic formalism introduced by Teodor Przymusinski in 1994. In this paper, we specialize it to a class of theories called `super logic programs'. We argue that these programs form a natural generalization of standard logic programs. In particula...
cs/0010033
A Formal Framework for Linguistic Annotation (revised version)
cs.CL cs.DB cs.DS
`Linguistic annotation' covers any descriptive or analytic notations applied to raw language data. The basic data may be in the form of time functions - audio, video and/or physiological recordings - or it may be textual. The added notations may include transcriptions of all sorts (from phonetic features to discourse...
cs/0010037
On the relationship between fuzzy logic and four-valued relevance logic
cs.AI
In fuzzy propositional logic, to a proposition a partial truth in [0,1] is assigned. It is well known that under certain circumstances, fuzzy logic collapses to classical logic. In this paper, we will show that under dual conditions, fuzzy logic collapses to four-valued (relevance) logic, where propositions have trut...
cs/0011001
Utilizing the World Wide Web as an Encyclopedia: Extracting Term Descriptions from Semi-Structured Texts
cs.CL
In this paper, we propose a method to extract descriptions of technical terms from Web pages in order to utilize the World Wide Web as an encyclopedia. We use linguistic patterns and HTML text structures to extract text fragments containing term descriptions. We also use a language model to discard extraneous descrip...
cs/0011002
A Novelty-based Evaluation Method for Information Retrieval
cs.CL
In information retrieval research, precision and recall have long been used to evaluate IR systems. However, given that a number of retrieval systems resembling one another are already available to the public, it is valuable to retrieve novel relevant documents, i.e., documents that cannot be retrieved by those exist...
cs/0011003
Applying Machine Translation to Two-Stage Cross-Language Information Retrieval
cs.CL
Cross-language information retrieval (CLIR), where queries and documents are in different languages, needs a translation of queries and/or documents, so as to standardize both of them into a common representation. For this purpose, the use of machine translation is an effective approach. However, computational cost i...
cs/0011007
Tree-gram Parsing: Lexical Dependencies and Structural Relations
cs.CL cs.AI cs.HC
This paper explores the kinds of probabilistic relations that are important in syntactic disambiguation. It proposes that two widely used kinds of relations, lexical dependencies and structural relations, have complementary disambiguation capabilities. It presents a new model based on structural relations, the Tree-g...
cs/0011008
A Lambda-Calculus with letrec, case, constructors and non-determinism
cs.PL cs.AI cs.SC
A non-deterministic call-by-need lambda-calculus \calc with case, constructors, letrec and a (non-deterministic) erratic choice, based on rewriting rules is investigated. A standard reduction is defined as a variant of left-most outermost reduction. The semantics is defined by contextual equivalence of expressions in...
cs/0011011
Formal Properties of XML Grammars and Languages
cs.DM cs.CL
XML documents are described by a document type definition (DTD). An XML-grammar is a formal grammar that captures the syntactic features of a DTD. We investigate properties of this family of grammars. We show that every XML-language basically has a unique XML-grammar. We give two characterizations of languages genera...
cs/0011012
Causes and Explanations: A Structural-Model Approach, Part I: Causes
cs.AI
We propose a new definition of actual cause, using structural equations to model counterfactuals. We show that the definition yields a plausible and elegant account of causation that handles well examples which have caused problems for other definitions and resolves major difficulties in the traditional account.
cs/0011014
Chip-level CMP Modeling and Smart Dummy for HDP and Conformal CVD Films
cs.CE
Chip-level CMP modeling is investigated to obtain the post-CMP film profile thickness across a die from its design layout file and a few film deposition and CMP parameters. The work covers both HDP and conformal CVD film. The experimental CMP results agree well with the modeled results. Different algorithms for filli...
cs/0011016
Designing Proxies for Stock Market Indices is Computationally Hard
cs.CE cs.CC
In this paper, we study the problem of designing proxies (or portfolios) for various stock market indices based on historical data. We use four different methods for computing market indices, all of which are formulas used in actual stock market analysis. For each index, we consider three criteria for designing the p...
cs/0011018
Optimal Buy-and-Hold Strategies for Financial Markets with Bounded Daily Returns
cs.CE cs.DS
In the context of investment analysis, we formulate an abstract online computing problem called a planning game and develop general tools for solving such a game. We then use the tools to investigate a practical buy-and-hold trading problem faced by long-term investors in stocks. We obtain the unique optimal static o...
cs/0011020
The Use of Instrumentation in Grammar Engineering
cs.CL
This paper explores the usefulness of a technique from software engineering, code instrumentation, for the development of large-scale natural language grammars. Information about the usage of grammar rules in test and corpus sentences is used to improve grammar and testsuite, as well as adapting a grammar to a specif...
cs/0011023
Optimal Bidding Algorithms Against Cheating in Multiple-Object Auctions
cs.CE cs.DS
This paper studies some basic problems in a multiple-object auction model using methodologies from theoretical computer science. We are especially concerned with situations where an adversary bidder knows the bidding algorithms of all the other bidders. In the two-bidder case, we derive an optimal randomized bidding ...
cs/0011024
Algorithms for Rewriting Aggregate Queries Using Views
cs.DB
Queries involving aggregation are typical in database applications. One of the main ideas to optimize the execution of an aggregate query is to reuse results of previously answered queries. This leads to the problem of rewriting aggregate queries using views. Due to a lack of theory, algorithms for this problem were ...
cs/0011028
Retrieval from Captioned Image Databases Using Natural Language Processing
cs.CL cs.IR
It might appear that natural language processing should improve the accuracy of information retrieval systems, by making available a more detailed analysis of queries and documents. Although past results appear to show that this is not so, if the focus is shifted to short phrases rather than full documents, the situa...
cs/0011030
Logic Programming Approaches for Representing and Solving Constraint Satisfaction Problems: A Comparison
cs.AI
Many logic programming based approaches can be used to describe and solve combinatorial search problems. On the one hand there is constraint logic programming which computes a solution as an answer substitution to a query containing the variables of the constraint satisfaction problem. On the other hand there are sys...
cs/0011032
Top-down induction of clustering trees
cs.LG
An approach to clustering is presented that adapts the basic top-down induction of decision trees method towards clustering. To this aim, it employs the principles of instance based learning. The resulting methodology is implemented in the TIC (Top down Induction of Clustering trees) system for first order clustering...
cs/0011033
Web Mining Research: A Survey
cs.LG cs.DB
With the huge amount of information available online, the World Wide Web is a fertile area for data mining research. The Web mining research is at the cross road of research from several research communities, such as database, information retrieval, and within AI, especially the sub-areas of machine learning and natu...
cs/0011034
Semantic interpretation of temporal information by abductive inference
cs.CL
Besides temporal information explicitly available in verbs and adjuncts, the temporal interpretation of a text also depends on general world knowledge and default assumptions. We will present a theory for describing the relation between, on the one hand, verbs, their tenses and adjuncts and, on the other, the eventua...
cs/0011035
Abductive reasoning with temporal information
cs.CL
Texts in natural language contain a lot of temporal information, both explicit and implicit. Verbs and temporal adjuncts carry most of the explicit information, but for a full understanding general world knowledge and default assumptions have to be taken into account. We will present a theory for describing the relat...
cs/0011038
Provably Fast and Accurate Recovery of Evolutionary Trees through Harmonic Greedy Triplets
cs.DS cs.LG
We give a greedy learning algorithm for reconstructing an evolutionary tree based on a certain harmonic average on triplets of terminal taxa. After the pairwise distances between terminal taxa are estimated from sequence data, the algorithm runs in O(n^2) time using O(n) work space, where n is the number of terminal ...
cs/0011040
Do All Fragments Count?
cs.CL
We aim at finding the minimal set of fragments which achieves maximal parse accuracy in Data Oriented Parsing. Experiments with the Penn Wall Street Journal treebank show that counts of almost arbitrary fragments within parse trees are important, leading to improved parse accuracy over previous models tested on this ...
cs/0011041
EquiX---A Search and Query Language for XML
cs.DB
EquiX is a search language for XML that combines the power of querying with the simplicity of searching. Requirements for such languages are discussed and it is shown that EquiX meets the necessary criteria. Both a graphical abstract syntax and a formal concrete syntax are presented for EquiX queries. In addition, th...
cs/0011042
Order-consistent programs are cautiously monotonic
cs.LO cs.AI
Some normal logic programs under the answer set (stable model) semantics lack the appealing property of "cautious monotonicity." That is, augmenting a program with one of its consequences may cause it to lose another of its consequences. The syntactic condition of "order-consistency" was shown by Fages to guarantee e...
cs/0011044
Scaling Up Inductive Logic Programming by Learning from Interpretations
cs.LG
When comparing inductive logic programming (ILP) and attribute-value learning techniques, there is a trade-off between expressive power and efficiency. Inductive logic programming techniques are typically more expressive but also less efficient. Therefore, the data sets handled by current inductive logic programming ...
cs/0012004
Improving Performance of heavily loaded agents
cs.MA cs.AI
With the increase in agent-based applications, there are now agent systems that support \emph{concurrent} client accesses. The ability to process large volumes of simultaneous requests is critical in many such applications. In such a setting, the traditional approach of serving these requests one at a time via queues...
cs/0012010
The Role of Commutativity in Constraint Propagation Algorithms
cs.PF cs.AI
Constraint propagation algorithms form an important part of most of the constraint programming systems. We provide here a simple, yet very general framework that allows us to explain several constraint propagation algorithms in a systematic way. In this framework we proceed in two steps. First, we introduce a generic...
cs/0012011
Towards a Universal Theory of Artificial Intelligence based on Algorithmic Probability and Sequential Decision Theory
cs.AI cs.CC cs.IT cs.LG math.IT
Decision theory formally solves the problem of rational agents in uncertain worlds if the true environmental probability distribution is known. Solomonoff's theory of universal induction formally solves the problem of sequence prediction for unknown distribution. We unify both theories and give strong arguments that ...
cs/0012020
Creativity and Delusions: A Neurocomputational Approach
cs.NE cs.AI
Thinking is one of the most interesting mental processes. Its complexity is sometimes simplified and its different manifestations are classified into normal and abnormal, like the delusional and disorganized thought or the creative one. The boundaries between these facets of thinking are fuzzy causing difficulties in...
cs/0012021
A Benchmark for Image Retrieval using Distributed Systems over the Internet: BIRDS-I
cs.IR cs.MM
The performance of CBIR algorithms is usually measured on an isolated workstation. In a real-world environment the algorithms would only constitute a minor component among the many interacting components. The Internet dramati-cally changes many of the usual assumptions about measuring CBIR performance. Any CBIR bench...
cs/0101010
An Even Faster and More Unifying Algorithm for Comparing Trees via Unbalanced Bipartite Matchings
cs.CV cs.DS
A widely used method for determining the similarity of two labeled trees is to compute a maximum agreement subtree of the two trees. Previous work on this similarity measure is only concerned with the comparison of labeled trees of two special kinds, namely, uniformly labeled trees (i.e., trees with all their nodes l...
cs/0101012
Communities of Practice in the Distributed International Environment
cs.HC cs.IR
Modern commercial organisations are facing pressures which have caused them to lose personnel. When they lose people, they also lose their knowledge. Organisations also have to cope with the internationalisation of business forcing collaboration and knowledge sharing across time and distance. Knowledge Management (KM...
cs/0101014
On the problem of computing the well-founded semantics
cs.LO cs.AI cs.DS
The well-founded semantics is one of the most widely studied and used semantics of logic programs with negation. In the case of finite propositional programs, it can be computed in polynomial time, more specifically, in O(|At(P)|size(P)) steps, where size(P) denotes the total number of occurrences of atoms in a logic...
cs/0101015
Combinatorial Toolbox for Protein Sequence Design and Landscape Analysis in the Grand Canonical Model
cs.CE cs.CC q-bio.BM
In modern biology, one of the most important research problems is to understand how protein sequences fold into their native 3D structures. To investigate this problem at a high level, one wishes to analyze the protein landscapes, i.e., the structures of the space of all protein sequences and their native 3D structur...
cs/0101016
A Dynamic Programming Approach to De Novo Peptide Sequencing via Tandem Mass Spectrometry
cs.CE cs.DS
The tandem mass spectrometry fragments a large number of molecules of the same peptide sequence into charged prefix and suffix subsequences, and then measures mass/charge ratios of these ions. The de novo peptide sequencing problem is to reconstruct the peptide sequence from a given tandem mass spectral data of k ion...
cs/0101019
General Loss Bounds for Universal Sequence Prediction
cs.AI cs.LG math.ST stat.TH
The Bayesian framework is ideally suited for induction problems. The probability of observing $x_t$ at time $t$, given past observations $x_1...x_{t-1}$ can be computed with Bayes' rule if the true distribution $\mu$ of the sequences $x_1x_2x_3...$ is known. The problem, however, is that in many cases one does not ev...
cs/0101030
Tree Contractions and Evolutionary Trees
cs.CE cs.DS
An evolutionary tree is a rooted tree where each internal vertex has at least two children and where the leaves are labeled with distinct symbols representing species. Evolutionary trees are useful for modeling the evolutionary history of species. An agreement subtree of two evolutionary trees is an evolutionary tree...
cs/0101031
Cavity Matchings, Label Compressions, and Unrooted Evolutionary Trees
cs.CE cs.DS
We present an algorithm for computing a maximum agreement subtree of two unrooted evolutionary trees. It takes O(n^{1.5} log n) time for trees with unbounded degrees, matching the best known time complexity for the rooted case. Our algorithm allows the input trees to be mixed trees, i.e., trees that may contain direc...
cs/0101034
Data Security Equals Graph Connectivity
cs.CR cs.DB cs.DS
To protect sensitive information in a cross tabulated table, it is a common practice to suppress some of the cells in the table. This paper investigates four levels of data security of a two-dimensional table concerning the effectiveness of this practice. These four levels of data security protect the information con...
cs/0101036
The Generalized Universal Law of Generalization
cs.CV cs.AI math.PR physics.soc-ph
It has been argued by Shepard that there is a robust psychological law that relates the distance between a pair of items in psychological space and the probability that they will be confused with each other. Specifically, the probability of confusion is a negative exponential function of the distance between the pair...
cs/0102002
On the Automated Classification of Web Sites
cs.IR
In this paper we discuss several issues related to automated text classification of web sites. We analyze the nature of web content and metadata in relation to requirements for text features. We find that HTML metatags are a good source of text features, but are not in wide use despite their role in search engine ran...
cs/0102003
Fast Pricing of European Asian Options with Provable Accuracy: Single-stock and Basket Options
cs.CE
This paper develops three polynomial-time pricing techniques for European Asian options with provably small errors, where the stock prices follow binomial trees or trees of higher-degree. The first technique is the first known Monte Carlo algorithm with analytical error bounds suitable for pricing single-stock option...
cs/0102008
Optimal Bid Sequences for Multiple-Object Auctions with Unequal Budgets
cs.CE cs.DM cs.DS
In a multiple-object auction, every bidder tries to win as many objects as possible with a bidding algorithm. This paper studies position-randomized auctions, which form a special class of multiple-object auctions where a bidding algorithm consists of an initial bid sequence and an algorithm for randomly permuting th...
cs/0102010
The Enhanced Double Digest Problem for DNA Physical Mapping
cs.CE cs.DM cs.DS
The double digest problem is a common NP-hard approach to constructing physical maps of DNA sequences. This paper presents a new approach called the enhanced double digest problem. Although this new problem is also NP-hard, it can be solved in linear time in certain theoretically interesting cases.
cs/0102011
A Price Dynamics in Bandwidth Markets for Point-to-point Connections
cs.NI cond-mat.soft cs.MA
We simulate a network of N routers and M network users making concurrent point-to-point connections by buying and selling router capacity from each other. The resources need to be acquired in complete sets, but there is only one spot market for each router. In order to describe the internal dynamics of the market, we...
cs/0102014
On the predictability of Rainfall in Kerala- An application of ABF Neural Network
cs.NE cs.AI
Rainfall in Kerala State, the southern part of Indian Peninsula in particular is caused by the two monsoons and the two cyclones every year. In general, climate and rainfall are highly nonlinear phenomena in nature giving rise to what is known as the `butterfly effect'. We however attempt to train an ABF neural netwo...
cs/0102015
Non-convex cost functionals in boosting algorithms and methods for panel selection
cs.NE cs.LG cs.NA math.NA
In this document we propose a new improvement for boosting techniques as proposed in Friedman '99 by the use of non-convex cost functional. The idea is to introduce a correlation term to better deal with forecasting of additive time series. The problem is discussed in a theoretical way to prove the existence of minim...
cs/0102018
An effective Procedure for Speeding up Algorithms
cs.CC cs.AI cs.LG
The provably asymptotically fastest algorithm within a factor of 5 for formally described problems will be constructed. The main idea is to enumerate all programs provably equivalent to the original problem by enumerating all proofs. The algorithm could be interpreted as a generalization and improvement of Levin sear...
cs/0102019
Easy and Hard Constraint Ranking in OT: Algorithms and Complexity
cs.CL cs.CC
We consider the problem of ranking a set of OT constraints in a manner consistent with data. We speed up Tesar and Smolensky's RCD algorithm to be linear on the number of constraints. This finds a ranking so each attested form x_i beats or ties a particular competitor y_i. We also generalize RCD so each x_i beats o...
cs/0102020
Multi-Syllable Phonotactic Modelling
cs.CL
This paper describes a novel approach to constructing phonotactic models. The underlying theoretical approach to phonological description is the multisyllable approach in which multiple syllable classes are defined that reflect phonotactically idiosyncratic syllable subcategories. A new finite-state formalism, OFS Mo...
cs/0102021
Taking Primitive Optimality Theory Beyond the Finite State
cs.CL
Primitive Optimality Theory (OTP) (Eisner, 1997a; Albro, 1998), a computational model of Optimality Theory (Prince and Smolensky, 1993), employs a finite state machine to represent the set of active candidates at each stage of an Optimality Theoretic derivation, as well as weighted finite state machines to represent ...
cs/0102022
Finite-State Phonology: Proceedings of the 5th Workshop of the ACL Special Interest Group in Computational Phonology (SIGPHON)
cs.CL
Home page of the workshop proceedings, with pointers to the individually archived papers. Includes front matter from the printed version of the proceedings.
cs/0102026
Mathematical Model of Word Length on the Basis of the Cebanov-Fucks Distribution with Uniform Parameter Distribution
cs.CL
The data on 13 typologically different languages have been processed using a two-parameter word length model, based on 1-displaced uniform Poisson distribution. Statistical dependencies of the 2nd parameter on the 1st one are revealed for the German texts and genre of letters.
cs/0102027
Gene Expression Programming: a New Adaptive Algorithm for Solving Problems
cs.AI cs.NE
Gene expression programming, a genotype/phenotype genetic algorithm (linear and ramified), is presented here for the first time as a new technique for the creation of computer programs. Gene expression programming uses character linear chromosomes composed of genes structurally organized in a head and a tail. The chr...
cs/0103002
Quantitative Neural Network Model of the Tip-of-the-Tongue Phenomenon Based on Synthesized Memory-Psycholinguistic-Metacognitive Approach
cs.CL cs.AI q-bio.NC q-bio.QM
A new three-stage computer artificial neural network model of the tip-of-the-tongue phenomenon is proposed. Each word's node is build from some interconnected learned auto-associative two-layer neural networks each of which represents separate word's semantic, lexical, or phonological components. The model synthesize...
cs/0103003
Learning Policies with External Memory
cs.LG
In order for an agent to perform well in partially observable domains, it is usually necessary for actions to depend on the history of observations. In this paper, we explore a {\it stigmergic} approach, in which the agent's actions include the ability to set and clear bits in an external memory, and the external mem...
cs/0103004
Rapid Application Evolution and Integration Through Document Metamorphosis
cs.DB
The Harland document management system implements a data model in which document (object) structure can be altered by mixin-style multiple inheritance at any time. This kind of structural fluidity has long been supported by knowledge-base management systems, but its use has primarily been in support of reasoning and ...