id stringlengths 9 16 | title stringlengths 4 278 | categories stringlengths 5 104 | abstract stringlengths 6 4.09k |
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cs/0005013 | Practical Reasoning for Very Expressive Description Logics | cs.LO cs.AI | Description Logics (DLs) are a family of knowledge representation formalisms
mainly characterised by constructors to build complex concepts and roles from
atomic ones. Expressive role constructors are important in many applications,
but can be computationally problematical. We present an algorithm that decides
satisf... |
cs/0005014 | Practical Reasoning for Expressive Description Logics | cs.LO cs.AI | Description Logics (DLs) are a family of knowledge representation formalisms
mainly characterised by constructors to build complex concepts and roles from
atomic ones. Expressive role constructors are important in many applications,
but can be computationally problematical. We present an algorithm that decides
satisf... |
cs/0005015 | Noun Phrase Recognition by System Combination | cs.CL | The performance of machine learning algorithms can be improved by combining
the output of different systems. In this paper we apply this idea to the
recognition of noun phrases.We generate different classifiers by using
different representations of the data. By combining the results with voting
techniques described i... |
cs/0005016 | Improving Testsuites via Instrumentation | cs.CL | This paper explores the usefulness of a technique from software engineering,
namely code instrumentation, for the development of large-scale natural
language grammars. Information about the usage of grammar rules in test
sentences is used to detect untested rules, redundant test sentences, and
likely causes of overge... |
cs/0005017 | Reasoning with Individuals for the Description Logic SHIQ | cs.LO cs.AI | While there has been a great deal of work on the development of reasoning
algorithms for expressive description logics, in most cases only Tbox reasoning
is considered. In this paper we present an algorithm for combined Tbox and Abox
reasoning in the SHIQ description logic. This algorithm is of particular
interest as... |
cs/0005019 | On the Scalability of the Answer Extraction System "ExtrAns" | cs.CL | This paper reports on the scalability of the answer extraction system
ExtrAns. An answer extraction system locates the exact phrases in the documents
that contain the explicit answers to the user queries. Answer extraction
systems are therefore more convenient than document retrieval systems in
situations where the u... |
cs/0005020 | Centroid-based summarization of multiple documents: sentence extraction,
utility-based evaluation, and user studies | cs.CL cs.AI cs.DL cs.HC cs.IR | We present a multi-document summarizer, called MEAD, which generates
summaries using cluster centroids produced by a topic detection and tracking
system. We also describe two new techniques, based on sentence utility and
subsumption, which we have applied to the evaluation of both single and
multiple document summari... |
cs/0005021 | Modeling the Uncertainty in Complex Engineering Systems | cs.AI cs.LG | Existing procedures for model validation have been deemed inadequate for many
engineering systems. The reason of this inadequacy is due to the high degree of
complexity of the mechanisms that govern these systems. It is proposed in this
paper to shift the attention from modeling the engineering system itself to
model... |
cs/0005024 | The SAT Phase Transition | cs.AI cs.CC | Phase transition is an important feature of SAT problem. For random k-SAT
model, it is proved that as r (ratio of clauses to variables) increases, the
structure of solutions will undergo a sudden change like satisfiability phase
transition when r reaches a threshold point. This phenomenon shows that the
satisfying tr... |
cs/0005025 | Finite-State Reduplication in One-Level Prosodic Morphology | cs.CL | Reduplication, a central instance of prosodic morphology, is particularly
challenging for state-of-the-art computational morphology, since it involves
copying of some part of a phonological string. In this paper I advocate a
finite-state method that combines enriched lexical representations via
intersection to implem... |
cs/0005026 | A One-Time Pad based Cipher for Data Protection in Distributed
Environments | cs.CR cs.DC cs.IR cs.NI | A one-time pad (OTP) based cipher to insure both data protection and
integrity when mobile code arrives to a remote host is presented. Data
protection is required when a mobile agent could retrieve confidential
information that would be encrypted in untrusted nodes of the network; in this
case, information management... |
cs/0005027 | A Bayesian Reflection on Surfaces | cs.CV cs.DS cs.LG math.PR nlin.AO physics.data-an | The topic of this paper is a novel Bayesian continuous-basis field
representation and inference framework. Within this paper several problems are
solved: The maximally informative inference of continuous-basis fields, that is
where the basis for the field is itself a continuous object and not
representable in a finit... |
cs/0005028 | A method for command identification, using modified collision free
hashing with addition & rotation iterative hash functions (part 1) | cs.HC cs.IR | This paper proposes a method for identification of a user`s fixed string set
(which can be a command/instruction set for a terminal or microprocessor). This
method is fast and has very small memory requirements, compared to a
traditional full string storage and compare method. The user feeds characters
into a microco... |
cs/0005029 | Ranking suspected answers to natural language questions using predictive
annotation | cs.CL | In this paper, we describe a system to rank suspected answers to natural
language questions. We process both corpus and query using a new technique,
predictive annotation, which augments phrases in texts with labels anticipating
their being targets of certain kinds of questions. Given a natural language
question, an ... |
cs/0005030 | Axiomatizing Causal Reasoning | cs.AI cs.LO | Causal models defined in terms of a collection of equations, as defined by
Pearl, are axiomatized here. Axiomatizations are provided for three
successively more general classes of causal models: (1) the class of recursive
theories (those without feedback), (2) the class of theories where the
solutions to the equation... |
cs/0005031 | Conditional Plausibility Measures and Bayesian Networks | cs.AI | A general notion of algebraic conditional plausibility measures is defined.
Probability measures, ranking functions, possibility measures, and (under the
appropriate definitions) sets of probability measures can all be viewed as
defining algebraic conditional plausibility measures. It is shown that
algebraic conditio... |
cs/0006001 | Boosting the Differences: A fast Bayesian classifier neural network | cs.CV | A Bayesian classifier that up-weights the differences in the attribute values
is discussed. Using four popular datasets from the UCI repository, some
interesting features of the network are illustrated. The network is suitable
for classification problems.
|
cs/0006002 | Distorted English Alphabet Identification : An application of Difference
Boosting Algorithm | cs.CV | The difference-boosting algorithm is used on letters dataset from the UCI
repository to classify distorted raster images of English alphabets. In
contrast to rather complex networks, the difference-boosting is found to
produce comparable or better classification efficiency on this complex problem.
|
cs/0006003 | Exploiting Diversity in Natural Language Processing: Combining Parsers | cs.CL | Three state-of-the-art statistical parsers are combined to produce more
accurate parses, as well as new bounds on achievable Treebank parsing accuracy.
Two general approaches are presented and two combination techniques are
described for each approach. Both parametric and non-parametric models are
explored. The resul... |
cs/0006005 | Novelty Detection for Robot Neotaxis | cs.RO cs.NE nlin.AO | The ability of a robot to detect and respond to changes in its environment is
potentially very useful, as it draws attention to new and potentially important
features. We describe an algorithm for learning to filter out previously
experienced stimuli to allow further concentration on novel features. The
algorithm use... |
cs/0006006 | A Real-Time Novelty Detector for a Mobile Robot | cs.RO cs.NE | Recognising new or unusual features of an environment is an ability which is
potentially very useful to a robot. This paper demonstrates an algorithm which
achieves this task by learning an internal representation of `normality' from
sonar scans taken as a robot explores the environment. This model of the
environment... |
cs/0006007 | Novelty Detection on a Mobile Robot Using Habituation | cs.RO cs.NE nlin.AO | In this paper a novelty filter is introduced which allows a robot operating
in an un structured environment to produce a self-organised model of its
surroundings and to detect deviations from the learned model. The environment
is perceived using the rob ot's 16 sonar sensors. The algorithm produces a
novelty measure ... |
cs/0006009 | Knowledge and common knowledge in a distributed environment | cs.DC cs.AI | Reasoning about knowledge seems to play a fundamental role in distributed
systems. Indeed, such reasoning is a central part of the informal intuitive
arguments used in the design of distributed protocols. Communication in a
distributed system can be viewed as the act of transforming the system's state
of knowledge. T... |
cs/0006011 | Bagging and Boosting a Treebank Parser | cs.CL | Bagging and boosting, two effective machine learning techniques, are applied
to natural language parsing. Experiments using these techniques with a
trainable statistical parser are described. The best resulting system provides
roughly as large of a gain in F-measure as doubling the corpus size. Error
analysis of the ... |
cs/0006012 | Exploiting Diversity for Natural Language Parsing | cs.CL | The popularity of applying machine learning methods to computational
linguistics problems has produced a large supply of trainable natural language
processing systems. Most problems of interest have an array of off-the-shelf
products or downloadable code implementing solutions using various techniques.
Where these so... |
cs/0006013 | An evaluation of Naive Bayesian anti-spam filtering | cs.CL cs.AI | It has recently been argued that a Naive Bayesian classifier can be used to
filter unsolicited bulk e-mail ("spam"). We conduct a thorough evaluation of
this proposal on a corpus that we make publicly available, contributing towards
standard benchmarks. At the same time we investigate the effect of
attribute-set size... |
cs/0006017 | Turning Speech Into Scripts | cs.CL | We describe an architecture for implementing spoken natural language dialogue
interfaces to semi-autonomous systems, in which the central idea is to
transform the input speech signal through successive levels of representation
corresponding roughly to linguistic knowledge, dialogue knowledge, and domain
knowledge. Th... |
cs/0006018 | Accuracy, Coverage, and Speed: What Do They Mean to Users? | cs.CL cs.HC | Speech is becoming increasingly popular as an interface modality, especially
in hands- and eyes-busy situations where the use of a keyboard or mouse is
difficult. However, despite the fact that many have hailed speech as being
inherently usable (since everyone already knows how to talk), most users of
speech input ar... |
cs/0006019 | A Compact Architecture for Dialogue Management Based on Scripts and
Meta-Outputs | cs.CL | We describe an architecture for spoken dialogue interfaces to semi-autonomous
systems that transforms speech signals through successive representations of
linguistic, dialogue, and domain knowledge. Each step produces an output, and a
meta-output describing the transformation, with an executable program in a
simple s... |
cs/0006020 | A Comparison of the XTAG and CLE Grammars for English | cs.CL | When people develop something intended as a large broad-coverage grammar,
they usually have a more specific goal in mind. Sometimes this goal is covering
a corpus; sometimes the developers have theoretical ideas they wish to
investigate; most often, work is driven by a combination of these two main
types of goal. Wha... |
cs/0006021 | Compiling Language Models from a Linguistically Motivated Unification
Grammar | cs.CL | Systems now exist which are able to compile unification grammars into
language models that can be included in a speech recognizer, but it is so far
unclear whether non-trivial linguistically principled grammars can be used for
this purpose. We describe a series of experiments which investigate the
question empiricall... |
cs/0006023 | Dialogue Act Modeling for Automatic Tagging and Recognition of
Conversational Speech | cs.CL | We describe a statistical approach for modeling dialogue acts in
conversational speech, i.e., speech-act-like units such as Statement, Question,
Backchannel, Agreement, Disagreement, and Apology. Our model detects and
predicts dialogue acts based on lexical, collocational, and prosodic cues, as
well as on the discour... |
cs/0006024 | Can Prosody Aid the Automatic Classification of Dialog Acts in
Conversational Speech? | cs.CL | Identifying whether an utterance is a statement, question, greeting, and so
forth is integral to effective automatic understanding of natural dialog.
Little is known, however, about how such dialog acts (DAs) can be automatically
classified in truly natural conversation. This study asks whether current
approaches, wh... |
cs/0006025 | Entropy-based Pruning of Backoff Language Models | cs.CL | A criterion for pruning parameters from N-gram backoff language models is
developed, based on the relative entropy between the original and the pruned
model. It is shown that the relative entropy resulting from pruning a single
N-gram can be computed exactly and efficiently for backoff models. The relative
entropy me... |
cs/0006027 | Verbal Interactions in Virtual Worlds | cs.CL cs.HC | We first discuss respective advantages of language interaction in virtual
worlds and of using 3D images in dialogue systems. Then, we describe an example
of a verbal interaction system in virtual reality: Ulysse. Ulysse is a
conversational agent that helps a user navigate in virtual worlds. It has been
designed to be... |
cs/0006028 | Trainable Methods for Surface Natural Language Generation | cs.CL | We present three systems for surface natural language generation that are
trainable from annotated corpora. The first two systems, called NLG1 and NLG2,
require a corpus marked only with domain-specific semantic attributes, while
the last system, called NLG3, requires a corpus marked with both semantic
attributes and... |
cs/0006030 | Multiagent Control of Self-reconfigurable Robots | cs.RO cs.DC cs.MA | We demonstrate how multiagent systems provide useful control techniques for
modular self-reconfigurable (metamorphic) robots. Such robots consist of many
modules that can move relative to each other, thereby changing the overall
shape of the robot to suit different tasks. Multiagent control is particularly
well-suite... |
cs/0006031 | Verifying Termination of General Logic Programs with Concrete Queries | cs.AI cs.LO | We introduce a method of verifying termination of logic programs with respect
to concrete queries (instead of abstract query patterns). A necessary and
sufficient condition is established and an algorithm for automatic verification
is developed. In contrast to existing query pattern-based approaches, our
method has t... |
cs/0006032 | Estimation of English and non-English Language Use on the WWW | cs.CL cs.HC | The World Wide Web has grown so big, in such an anarchic fashion, that it is
difficult to describe. One of the evident intrinsic characteristics of the
World Wide Web is its multilinguality. Here, we present a technique for
estimating the size of a language-specific corpus given the frequency of
commonly occurring wo... |
cs/0006036 | Prosody-Based Automatic Segmentation of Speech into Sentences and Topics | cs.CL | A crucial step in processing speech audio data for information extraction,
topic detection, or browsing/playback is to segment the input into sentence and
topic units. Speech segmentation is challenging, since the cues typically
present for segmenting text (headers, paragraphs, punctuation) are absent in
spoken langu... |
cs/0006038 | Approximation and Exactness in Finite State Optimality Theory | cs.CL | Previous work (Frank and Satta 1998; Karttunen, 1998) has shown that
Optimality Theory with gradient constraints generally is not finite state. A
new finite-state treatment of gradient constraints is presented which improves
upon the approximation of Karttunen (1998). The method turns out to be exact,
and very compac... |
cs/0006039 | Orthogonal Least Squares Algorithm for the Approximation of a Map and
its Derivatives with a RBF Network | cs.NE cs.SD | Radial Basis Function Networks (RBFNs) are used primarily to solve
curve-fitting problems and for non-linear system modeling. Several algorithms
are known for the approximation of a non-linear curve from a sparse data set by
means of RBFNs. However, there are no procedures that permit to define
constrains on the deri... |
cs/0006040 | Correlation over Decomposed Signals: A Non-Linear Approach to Fast and
Effective Sequences Comparison | cs.CV cs.DS q-bio | A novel non-linear approach to fast and effective comparison of sequences is
presented, compared to the traditional cross-correlation operator, and
illustrated with respect to DNA sequences.
|
cs/0006041 | Using a Diathesis Model for Semantic Parsing | cs.CL cs.AI | This paper presents a semantic parsing approach for unrestricted texts.
Semantic parsing is one of the major bottlenecks of Natural Language
Understanding (NLU) systems and usually requires building expensive resources
not easily portable to other domains. Our approach obtains a case-role
analysis, in which the seman... |
cs/0006042 | Semantic Parsing based on Verbal Subcategorization | cs.CL cs.AI | The aim of this work is to explore new methodologies on Semantic Parsing for
unrestricted texts. Our approach follows the current trends in Information
Extraction (IE) and is based on the application of a verbal subcategorization
lexicon (LEXPIR) by means of complex pattern recognition techniques. LEXPIR is
framed on... |
cs/0006043 | Constraint compiling into rules formalism constraint compiling into
rules formalism for dynamic CSPs computing | cs.AI | In this paper we present a rule based formalism for filtering variables
domains of constraints. This formalism is well adapted for solving dynamic CSP.
We take diagnosis as an instance problem to illustrate the use of these rules.
A diagnosis problem is seen like finding all the minimal sets of constraints to
be rela... |
cs/0006044 | Finite-State Non-Concatenative Morphotactics | cs.CL | Finite-state morphology in the general tradition of the Two-Level and Xerox
implementations has proved very successful in the production of robust
morphological analyzer-generators, including many large-scale commercial
systems. However, it has long been recognized that these implementations have
serious limitations ... |
cs/0006047 | Geometric Morphology of Granular Materials | cs.CV | We present a new method to transform the spectral pixel information of a
micrograph into an affine geometric description, which allows us to analyze the
morphology of granular materials. We use spectral and pulse-coupled neural
network based segmentation techniques to generate blobs, and a newly developed
algorithm t... |
cs/0007001 | Constraint Exploration and Envelope of Simulation Trajectories | cs.PL cs.AI cs.LO | The implicit theory that a simulation represents is precisely not in the
individual choices but rather in the 'envelope' of possible trajectories - what
is important is the shape of the whole envelope. Typically a huge amount of
computation is required when experimenting with factors bearing on the dynamics
of a simu... |
cs/0007002 | Interval Constraint Solving for Camera Control and Motion Planning | cs.AI cs.NA math.NA | Many problems in robust control and motion planning can be reduced to either
find a sound approximation of the solution space determined by a set of
nonlinear inequalities, or to the ``guaranteed tuning problem'' as defined by
Jaulin and Walter, which amounts to finding a value for some tuning parameter
such that a s... |
cs/0007003 | Using compression to identify acronyms in text | cs.DL cs.IR | Text mining is about looking for patterns in natural language text, and may
be defined as the process of analyzing text to extract information from it for
particular purposes. In previous work, we claimed that compression is a key
technology for text mining, and backed this up with a study that showed how
particular ... |
cs/0007004 | Brainstorm/J: a Java Framework for Intelligent Agents | cs.AI | Despite the effort of many researchers in the area of multi-agent systems
(MAS) for designing and programming agents, a few years ago the research
community began to take into account that common features among different MAS
exists. Based on these common features, several tools have tackled the problem
of agent devel... |
cs/0007009 | Incremental construction of minimal acyclic finite-state automata | cs.CL | In this paper, we describe a new method for constructing minimal,
deterministic, acyclic finite-state automata from a set of strings. Traditional
methods consist of two phases: the first to construct a trie, the second one to
minimize it. Our approach is to construct a minimal automaton in a single phase
by adding ne... |
cs/0007010 | Boosting Applied to Word Sense Disambiguation | cs.CL cs.AI | In this paper Schapire and Singer's AdaBoost.MH boosting algorithm is applied
to the Word Sense Disambiguation (WSD) problem. Initial experiments on a set of
15 selected polysemous words show that the boosting approach surpasses Naive
Bayes and Exemplar-based approaches, which represent state-of-the-art accuracy
on s... |
cs/0007011 | Naive Bayes and Exemplar-Based approaches to Word Sense Disambiguation
Revisited | cs.CL cs.AI | This paper describes an experimental comparison between two standard
supervised learning methods, namely Naive Bayes and Exemplar-based
classification, on the Word Sense Disambiguation (WSD) problem. The aim of the
work is twofold. Firstly, it attempts to contribute to clarify some confusing
information about the com... |
cs/0007012 | Using Learning-based Filters to Detect Rule-based Filtering Obsolescence | cs.CL cs.AI | For years, Caisse des Depots et Consignations has produced information
filtering applications. To be operational, these applications require high
filtering performances which are achieved by using rule-based filters. With
this technique, an administrator has to tune a set of rules for each topic.
However, filters bec... |
cs/0007013 | Applying Constraint Handling Rules to HPSG | cs.CL cs.PL | Constraint Handling Rules (CHR) have provided a realistic solution to an
over-arching problem in many fields that deal with constraint logic
programming: how to combine recursive functions or relations with constraints
while avoiding non-termination problems. This paper focuses on some other
benefits that CHR, specif... |
cs/0007016 | Two Steps Feature Selection and Neural Network Classification for the
TREC-8 Routing | cs.CL cs.AI | For the TREC-8 routing, one specific filter is built for each topic. Each
filter is a classifier trained to recognize the documents that are relevant to
the topic. When presented with a document, each classifier estimates the
probability for the document to be relevant to the topic for which it has been
trained. Sinc... |
cs/0007017 | Fuzzy data: XML may handle it | cs.IR | Data modeling is one of the most difficult tasks in application engineering.
The engineer must be aware of the use cases and the required application
services and at a certain point of time he has to fix the data model which
forms the base for the application services. However, once the data model has
been fixed it i... |
cs/0007018 | Bootstrapping a Tagged Corpus through Combination of Existing
Heterogeneous Taggers | cs.CL | This paper describes a new method, Combi-bootstrap, to exploit existing
taggers and lexical resources for the annotation of corpora with new tagsets.
Combi-bootstrap uses existing resources as features for a second level machine
learning module, that is trained to make the mapping to the new tagset on a
very small sa... |
cs/0007020 | Polynomial-time Computation via Local Inference Relations | cs.LO cs.AI cs.PL | We consider the concept of a local set of inference rules. A local rule set
can be automatically transformed into a rule set for which bottom-up evaluation
terminates in polynomial time. The local-rule-set transformation gives
polynomial-time evaluation strategies for a large variety of rule sets that
cannot be given... |
cs/0007022 | ATLAS: A flexible and extensible architecture for linguistic annotation | cs.CL | We describe a formal model for annotating linguistic artifacts, from which we
derive an application programming interface (API) to a suite of tools for
manipulating these annotations. The abstract logical model provides for a range
of storage formats and promotes the reuse of tools that interact through this
API. We ... |
cs/0007023 | Towards a query language for annotation graphs | cs.CL cs.DB | The multidimensional, heterogeneous, and temporal nature of speech databases
raises interesting challenges for representation and query. Recently,
annotation graphs have been proposed as a general-purpose representational
framework for speech databases. Typical queries on annotation graphs require
path expressions si... |
cs/0007024 | Many uses, many annotations for large speech corpora: Switchboard and
TDT as case studies | cs.CL | This paper discusses the challenges that arise when large speech corpora
receive an ever-broadening range of diverse and distinct annotations. Two case
studies of this process are presented: the Switchboard Corpus of telephone
conversations and the TDT2 corpus of broadcast news. Switchboard has undergone
two independ... |
cs/0007026 | Integrating E-Commerce and Data Mining: Architecture and Challenges | cs.LG cs.AI cs.CV cs.DB | We show that the e-commerce domain can provide all the right ingredients for
successful data mining and claim that it is a killer domain for data mining. We
describe an integrated architecture, based on our expe-rience at Blue Martini
Software, for supporting this integration. The architecture can dramatically
reduce... |
cs/0007031 | Parameter-free Model of Rank Polysemantic Distribution | cs.CL | A model of rank polysemantic distribution with a minimal number of fitting
parameters is offered. In an ideal case a parameter-free description of the
dependence on the basis of one or several immediate features of the
distribution is possible.
|
cs/0007032 | Knowledge on Treelike Spaces | cs.LO cs.AI | This paper presents a bimodal logic for reasoning about knowledge during
knowledge acquisition. One of the modalities represents (effort during)
non-deterministic time and the other represents knowledge. The semantics of
this logic are tree-like spaces which are a generalization of semantics used
for modeling branchi... |
cs/0007033 | To Preference via Entrenchment | cs.LO cs.AI | We introduce a simple generalization of Gardenfors and Makinson's epistemic
entrenchment called partial entrenchment. We show that preferential inference
can be generated as the sceptical counterpart of an inference mechanism defined
directly on partial entrenchment.
|
cs/0007035 | Mapping WordNets Using Structural Information | cs.CL | We present a robust approach for linking already existing lexical/semantic
hierarchies. We used a constraint satisfaction algorithm (relaxation labeling)
to select --among a set of candidates-- the node in a target taxonomy that
bests matches each node in a source taxonomy. In particular, we use it to map
the nominal... |
cs/0007036 | Language identification of controlled systems: Modelling, control and
anomaly detection | cs.CL | Formal language techniques have been used in the past to study autonomous
dynamical systems. However, for controlled systems, new features are needed to
distinguish between information generated by the system and input control. We
show how the modelling framework for controlled dynamical systems leads
naturally to a ... |
cs/0007038 | Modal Logics for Topological Spaces | cs.LO cs.AI | In this thesis we shall present two logical systems, MP and MP, for the
purpose of reasoning about knowledge and effort. These logical systems will be
interpreted in a spatial context and therefore, the abstract concepts of
knowledge and effort will be defined by concrete mathematical concepts.
|
cs/0007039 | Ordering-based Representations of Rational Inference | cs.LO cs.AI | Rational inference relations were introduced by Lehmann and Magidor as the
ideal systems for drawing conclusions from a conditional base. However, there
has been no simple characterization of these relations, other than its original
representation by preferential models. In this paper, we shall characterize
them with... |
cs/0007040 | Entrenchment Relations: A Uniform Approach to Nonmonotonicity | cs.LO cs.AI | We show that Gabbay's nonmonotonic consequence relations can be reduced to a
new family of relations, called entrenchment relations. Entrenchment relations
provide a direct generalization of epistemic entrenchment and expectation
ordering introduced by Gardenfors and Makinson for the study of belief revision
and expe... |
cs/0007041 | Relevance as Deduction: A Logical View of Information Retrieval | cs.IR cs.LO | The problem of Information Retrieval is, given a set of documents D and a
query q, providing an algorithm for retrieving all documents in D relevant to
q. However, retrieval should depend and be updated whenever the user is able to
provide as an input a preferred set of relevant documents; this process is
known as em... |
cs/0007044 | Managing Periodically Updated Data in Relational Databases: A Stochastic
Modeling Approach | cs.DB | Recent trends in information management involve the periodic transcription of
data onto secondary devices in a networked environment, and the proper
scheduling of these transcriptions is critical for efficient data management.
To assist in the scheduling process, we are interested in modeling the
reduction of consist... |
cs/0008003 | Interfacing Constraint-Based Grammars and Generation Algorithms | cs.CL | Constraint-based grammars can, in principle, serve as the major linguistic
knowledge source for both parsing and generation. Surface generation starts
from input semantics representations that may vary across grammars. For many
declarative grammars, the concept of derivation implicitly built in is that of
parsing. Th... |
cs/0008004 | Comparing two trainable grammatical relations finders | 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. On such a small training corpus, we compare two
systems. They ... |
cs/0008005 | More accurate tests for the statistical significance of result
differences | cs.CL | Statistical significance testing of differences in values of metrics like
recall, precision and balanced F-score is a necessary part of empirical natural
language processing. Unfortunately, we find in a set of experiments that many
commonly used tests often underestimate the significance and so are less likely
to det... |
cs/0008007 | Tagger Evaluation Given Hierarchical Tag Sets | cs.CL | We present methods for evaluating human and automatic taggers that extend
current practice in three ways. First, we show how to evaluate taggers that
assign multiple tags to each test instance, even if they do not assign
probabilities. Second, we show how to accommodate a common property of manually
constructed ``gol... |
cs/0008008 | On the Average Similarity Degree between Solutions of Random k-SAT and
Random CSPs | cs.AI cs.CC cs.DM | To study the structure of solutions for random k-SAT and random CSPs, this
paper introduces the concept of average similarity degree to characterize how
solutions are similar to each other. It is proved that under certain
conditions, as r (i.e. the ratio of constraints to variables) increases, the
limit of average si... |
cs/0008009 | Data Mining to Measure and Improve the Success of Web Sites | cs.LG cs.DB | For many companies, competitiveness in e-commerce requires a successful
presence on the web. Web sites are used to establish the company's image, to
promote and sell goods and to provide customer support. The success of a web
site affects and reflects directly the success of the company in the electronic
market. In t... |
cs/0008012 | Applying System Combination to Base Noun Phrase Identification | cs.CL | We use seven machine learning algorithms for one task: identifying base noun
phrases. The results have been processed by different system combination
methods and all of these outperformed the best individual result. We have
applied the seven learners with the best combinator, a majority vote of the top
five systems, ... |
cs/0008013 | Meta-Learning for Phonemic Annotation of Corpora | cs.CL | We apply rule induction, classifier combination and meta-learning (stacked
classifiers) to the problem of bootstrapping high accuracy automatic annotation
of corpora with pronunciation information. The task we address in this paper
consists of generating phonemic representations reflecting the Flemish and
Dutch pronu... |
cs/0008014 | Aspects of Pattern-Matching in Data-Oriented Parsing | cs.CL | Data-Oriented Parsing (dop) ranks among the best parsing schemes, pairing
state-of-the art parsing accuracy to the psycholinguistic insight that larger
chunks of syntactic structures are relevant grammatical and probabilistic
units. Parsing with the dop-model, however, seems to involve a lot of CPU
cycles and a consi... |
cs/0008015 | Temiar Reduplication in One-Level Prosodic Morphology | cs.CL | Temiar reduplication is a difficult piece of prosodic morphology. This paper
presents the first computational analysis of Temiar reduplication, using the
novel finite-state approach of One-Level Prosodic Morphology originally
developed by Walther (1999b, 2000). After reviewing both the data and the basic
tenets of On... |
cs/0008016 | Processing Self Corrections in a speech to speech system | cs.CL cs.AI | Speech repairs occur often in spontaneous spoken dialogues. The ability to
detect and correct those repairs is necessary for any spoken language system.
We present a framework to detect and correct speech repairs where all relevant
levels of information, i.e., acoustics, lexis, syntax and semantics can be
integrated.... |
cs/0008017 | Efficient probabilistic top-down and left-corner parsing | cs.CL | This paper examines efficient predictive broad-coverage parsing without
dynamic programming. In contrast to bottom-up methods, depth-first top-down
parsing produces partial parses that are fully connected trees spanning the
entire left context, from which any kind of non-local dependency or partial
semantic interpret... |
cs/0008019 | An Experimental Comparison of Naive Bayesian and Keyword-Based Anti-Spam
Filtering with Personal E-mail Messages | cs.CL cs.IR cs.LG | The growing problem of unsolicited bulk e-mail, also known as "spam", has
generated a need for reliable anti-spam e-mail filters. Filters of this type
have so far been based mostly on manually constructed keyword patterns. An
alternative approach has recently been proposed, whereby a Naive Bayesian
classifier is trai... |
cs/0008020 | Explaining away ambiguity: Learning verb selectional preference with
Bayesian networks | cs.CL cs.AI | This paper presents a Bayesian model for unsupervised learning of verb
selectional preferences. For each verb the model creates a Bayesian network
whose architecture is determined by the lexical hierarchy of Wordnet and whose
parameters are estimated from a list of verb-object pairs found from a corpus.
``Explaining ... |
cs/0008021 | Compact non-left-recursive grammars using the selective left-corner
transform and factoring | cs.CL | The left-corner transform removes left-recursion from (probabilistic)
context-free grammars and unification grammars, permitting simple top-down
parsing techniques to be used. Unfortunately the grammars produced by the
standard left-corner transform are usually much larger than the original. The
selective left-corner... |
cs/0008022 | A Learning Approach to Shallow Parsing | cs.LG cs.CL | A SNoW based learning approach to shallow parsing tasks is presented and
studied experimentally. The approach learns to identify syntactic patterns by
combining simple predictors to produce a coherent inference. Two instantiations
of this approach are studied and experimental results for Noun-Phrases (NP) and
Subject... |
cs/0008023 | Selectional Restrictions in HPSG | cs.CL | Selectional restrictions are semantic sortal constraints imposed on the
participants of linguistic constructions to capture contextually-dependent
constraints on interpretation. Despite their limitations, selectional
restrictions have proven very useful in natural language applications, where
they have been used freq... |
cs/0008024 | Estimation of Stochastic Attribute-Value Grammars using an Informative
Sample | cs.CL | We argue that some of the computational complexity associated with estimation
of stochastic attribute-value grammars can be reduced by training upon an
informative subset of the full training set. Results using the parsed Wall
Street Journal corpus show that in some circumstances, it is possible to obtain
better esti... |
cs/0008026 | Noun-phrase co-occurrence statistics for semi-automatic semantic lexicon
construction | cs.CL | Generating semantic lexicons semi-automatically could be a great time saver,
relative to creating them by hand. In this paper, we present an algorithm for
extracting potential entries for a category from an on-line corpus, based upon
a small set of exemplars. Our algorithm finds more correct terms and fewer
incorrect... |
cs/0008027 | Measuring efficiency in high-accuracy, broad-coverage statistical
parsing | cs.CL | Very little attention has been paid to the comparison of efficiency between
high accuracy statistical parsers. This paper proposes one machine-independent
metric that is general enough to allow comparisons across very different
parsing architectures. This metric, which we call ``events considered'',
measures the numb... |
cs/0008028 | Estimators for Stochastic ``Unification-Based'' Grammars | cs.CL | Log-linear models provide a statistically sound framework for Stochastic
``Unification-Based'' Grammars (SUBGs) and stochastic versions of other kinds
of grammars. We describe two computationally-tractable ways of estimating the
parameters of such grammars from a training corpus of syntactic analyses, and
apply these... |
cs/0008029 | Exploiting auxiliary distributions in stochastic unification-based
grammars | cs.CL | This paper describes a method for estimating conditional probability
distributions over the parses of ``unification-based'' grammars which can
utilize auxiliary distributions that are estimated by other means. We show how
this can be used to incorporate information about lexical selectional
preferences gathered from ... |
cs/0008030 | Metonymy Interpretation Using X NO Y Examples | cs.CL | We developed on example-based method of metonymy interpretation. One
advantages of this method is that a hand-built database of metonymy is not
necessary because it instead uses examples in the form ``Noun X no Noun Y (Noun
Y of Noun X).'' Another advantage is that we will be able to interpret
newly-coined metonymic ... |
cs/0008031 | Bunsetsu Identification Using Category-Exclusive Rules | cs.CL | This paper describes two new bunsetsu identification methods using supervised
learning. Since Japanese syntactic analysis is usually done after bunsetsu
identification, bunsetsu identification is important for analyzing Japanese
sentences. In experiments comparing the four previously available
machine-learning method... |
cs/0008032 | Japanese Probabilistic Information Retrieval Using Location and Category
Information | cs.CL | Robertson's 2-poisson information retrieve model does not use location and
category information. We constructed a framework using location and category
information in a 2-poisson model. We submitted two systems based on this
framework to the IREX contest, Japanese language information retrieval contest
held in Japan ... |
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