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cs/9905001
|
Supervised Grammar Induction Using Training Data with Limited
Constituent Information
|
cs.CL
|
Corpus-based grammar induction generally relies on hand-parsed training data
to learn the structure of the language. Unfortunately, the cost of building
large annotated corpora is prohibitively expensive. This work aims to improve
the induction strategy when there are few labels in the training data. We show
that the most informative linguistic constituents are the higher nodes in the
parse trees, typically denoting complex noun phrases and sentential clauses.
They account for only 20% of all constituents. For inducing grammars from
sparsely labeled training data (e.g., only higher-level constituent labels), we
propose an adaptation strategy, which produces grammars that parse almost as
well as grammars induced from fully labeled corpora. Our results suggest that
for a partial parser to replace human annotators, it must be able to
automatically extract higher-level constituents rather than base noun phrases.
|
cs/9905003
|
Collective Choice Theory in Collaborative Computing
|
cs.MA cs.DC
|
This paper presents some fundamental collective choice theory for information
system designers, particularly those working in the field of computer-supported
cooperative work. This paper is focused on a presentation of Arrow's
Possibility and Impossibility theorems which form the fundamental boundary on
the efficacy of collective choice: voting and selection procedures. It restates
the conditions that Arrow placed on collective choice functions in more
rigorous second-order logic, which could be used as a set of test conditions
for implementations, and a useful probabilistic result for analyzing votes on
issue pairs. It also describes some simple collective choice functions. There
is also some discussion of how enterprises should approach putting their
resources under collective control: giving an outline of a superstructure of
performative agents to carry out this function and what distributing processing
technology would be needed.
|
cs/9905004
|
Using Collective Intelligence to Route Internet Traffic
|
cs.LG adap-org cond-mat.stat-mech cs.DC cs.NI nlin.AO
|
A COllective INtelligence (COIN) is a set of interacting reinforcement
learning (RL) algorithms designed in an automated fashion so that their
collective behavior optimizes a global utility function. We summarize the
theory of COINs, then present experiments using that theory to design COINs to
control internet traffic routing. These experiments indicate that COINs
outperform all previously investigated RL-based, shortest path routing
algorithms.
|
cs/9905005
|
General Principles of Learning-Based Multi-Agent Systems
|
cs.MA adap-org cond-mat.stat-mech cs.DC cs.LG nlin.AO
|
We consider the problem of how to design large decentralized multi-agent
systems (MAS's) in an automated fashion, with little or no hand-tuning. Our
approach has each agent run a reinforcement learning algorithm. This converts
the problem into one of how to automatically set/update the reward functions
for each of the agents so that the global goal is achieved. In particular we do
not want the agents to ``work at cross-purposes'' as far as the global goal is
concerned. We use the term artificial COllective INtelligence (COIN) to refer
to systems that embody solutions to this problem. In this paper we present a
summary of a mathematical framework for COINs. We then investigate the
real-world applicability of the core concepts of that framework via two
computer experiments: we show that our COINs perform near optimally in a
difficult variant of Arthur's bar problem (and in particular avoid the tragedy
of the commons for that problem), and we also illustrate optimal performance
for our COINs in the leader-follower problem.
|
cs/9905007
|
An Efficient, Probabilistically Sound Algorithm for Segmentation and
Word Discovery
|
cs.CL cs.LG
|
This paper presents a model-based, unsupervised algorithm for recovering word
boundaries in a natural-language text from which they have been deleted. The
algorithm is derived from a probability model of the source that generated the
text. The fundamental structure of the model is specified abstractly so that
the detailed component models of phonology, word-order, and word frequency can
be replaced in a modular fashion. The model yields a language-independent,
prior probability distribution on all possible sequences of all possible words
over a given alphabet, based on the assumption that the input was generated by
concatenating words from a fixed but unknown lexicon. The model is unusual in
that it treats the generation of a complete corpus, regardless of length, as a
single event in the probability space. Accordingly, the algorithm does not
estimate a probability distribution on words; instead, it attempts to calculate
the prior probabilities of various word sequences that could underlie the
observed text. Experiments on phonemic transcripts of spontaneous speech by
parents to young children suggest that this algorithm is more effective than
other proposed algorithms, at least when utterance boundaries are given and the
text includes a substantial number of short utterances.
Keywords: Bayesian grammar induction, probability models, minimum description
length (MDL), unsupervised learning, cognitive modeling, language acquisition,
segmentation
|
cs/9905008
|
Inducing a Semantically Annotated Lexicon via EM-Based Clustering
|
cs.CL cs.AI cs.LG
|
We present a technique for automatic induction of slot annotations for
subcategorization frames, based on induction of hidden classes in the EM
framework of statistical estimation. The models are empirically evalutated by a
general decision test. Induction of slot labeling for subcategorization frames
is accomplished by a further application of EM, and applied experimentally on
frame observations derived from parsing large corpora. We outline an
interpretation of the learned representations as theoretical-linguistic
decompositional lexical entries.
|
cs/9905009
|
Inside-Outside Estimation of a Lexicalized PCFG for German
|
cs.CL cs.LG
|
The paper describes an extensive experiment in inside-outside estimation of a
lexicalized probabilistic context free grammar for German verb-final clauses.
Grammar and formalism features which make the experiment feasible are
described. Successive models are evaluated on precision and recall of phrase
markup.
|
cs/9905010
|
Statistical Inference and Probabilistic Modelling for Constraint-Based
NLP
|
cs.CL cs.LG
|
We present a probabilistic model for constraint-based grammars and a method
for estimating the parameters of such models from incomplete, i.e., unparsed
data. Whereas methods exist to estimate the parameters of probabilistic
context-free grammars from incomplete data (Baum 1970), so far for
probabilistic grammars involving context-dependencies only parameter estimation
techniques from complete, i.e., fully parsed data have been presented (Abney
1997). However, complete-data estimation requires labor-intensive, error-prone,
and grammar-specific hand-annotating of large language corpora. We present a
log-linear probability model for constraint logic programming, and a general
algorithm to estimate the parameters of such models from incomplete data by
extending the estimation algorithm of Della-Pietra, Della-Pietra, and Lafferty
(1997) to incomplete data settings.
|
cs/9905011
|
Ensembles of Radial Basis Function Networks for Spectroscopic Detection
of Cervical Pre-Cancer
|
cs.NE cs.LG q-bio
|
The mortality related to cervical cancer can be substantially reduced through
early detection and treatment. However, current detection techniques, such as
Pap smear and colposcopy, fail to achieve a concurrently high sensitivity and
specificity.
In vivo fluorescence spectroscopy is a technique which quickly,
non-invasively and quantitatively probes the biochemical and morphological
changes that occur in pre-cancerous tissue.
A multivariate statistical algorithm was used to extract clinically useful
information from tissue spectra acquired from 361 cervical sites from 95
patients at 337, 380 and 460 nm excitation wavelengths. The multivariate
statistical analysis was also employed to reduce the number of fluorescence
excitation-emission wavelength pairs required to discriminate healthy tissue
samples from pre-cancerous tissue samples. The use of connectionist methods
such as multi layered perceptrons, radial basis function networks, and
ensembles of such networks was investigated. RBF ensemble algorithms based on
fluorescence spectra potentially provide automated, and near real-time
implementation of pre-cancer detection in the hands of non-experts. The results
are more reliable, direct and accurate than those achieved by either human
experts or multivariate statistical algorithms.
|
cs/9905012
|
Linear and Order Statistics Combiners for Pattern Classification
|
cs.NE cs.LG
|
Several researchers have experimentally shown that substantial improvements
can be obtained in difficult pattern recognition problems by combining or
integrating the outputs of multiple classifiers. This chapter provides an
analytical framework to quantify the improvements in classification results due
to combining. The results apply to both linear combiners and order statistics
combiners. We first show that to a first order approximation, the error rate
obtained over and above the Bayes error rate, is directly proportional to the
variance of the actual decision boundaries around the Bayes optimum boundary.
Combining classifiers in output space reduces this variance, and hence reduces
the "added" error. If N unbiased classifiers are combined by simple averaging,
the added error rate can be reduced by a factor of N if the individual errors
in approximating the decision boundaries are uncorrelated. Expressions are then
derived for linear combiners which are biased or correlated, and the effect of
output correlations on ensemble performance is quantified. For order statistics
based non-linear combiners, we derive expressions that indicate how much the
median, the maximum and in general the ith order statistic can improve
classifier performance. The analysis presented here facilitates the
understanding of the relationships among error rates, classifier boundary
distributions, and combining in output space. Experimental results on several
public domain data sets are provided to illustrate the benefits of combining
and to support the analytical results.
|
cs/9905013
|
Robust Combining of Disparate Classifiers through Order Statistics
|
cs.LG cs.CV cs.NE
|
Integrating the outputs of multiple classifiers via combiners or
meta-learners has led to substantial improvements in several difficult pattern
recognition problems. In the typical setting investigated till now, each
classifier is trained on data taken or resampled from a common data set, or
(almost) randomly selected subsets thereof, and thus experiences similar
quality of training data. However, in certain situations where data is acquired
and analyzed on-line at several geographically distributed locations, the
quality of data may vary substantially, leading to large discrepancies in
performance of individual classifiers. In this article we introduce and
investigate a family of classifiers based on order statistics, for robust
handling of such cases. Based on a mathematical modeling of how the decision
boundaries are affected by order statistic combiners, we derive expressions for
the reductions in error expected when such combiners are used. We show
analytically that the selection of the median, the maximum and in general, the
$i^{th}$ order statistic improves classification performance. Furthermore, we
introduce the trim and spread combiners, both based on linear combinations of
the ordered classifier outputs, and show that they are quite beneficial in
presence of outliers or uneven classifier performance. Experimental results on
several public domain data sets corroborate these findings.
|
cs/9905014
|
Hierarchical Reinforcement Learning with the MAXQ Value Function
Decomposition
|
cs.LG
|
This paper presents the MAXQ approach to hierarchical reinforcement learning
based on decomposing the target Markov decision process (MDP) into a hierarchy
of smaller MDPs and decomposing the value function of the target MDP into an
additive combination of the value functions of the smaller MDPs. The paper
defines the MAXQ hierarchy, proves formal results on its representational
power, and establishes five conditions for the safe use of state abstractions.
The paper presents an online model-free learning algorithm, MAXQ-Q, and proves
that it converges wih probability 1 to a kind of locally-optimal policy known
as a recursively optimal policy, even in the presence of the five kinds of
state abstraction. The paper evaluates the MAXQ representation and MAXQ-Q
through a series of experiments in three domains and shows experimentally that
MAXQ-Q (with state abstractions) converges to a recursively optimal policy much
faster than flat Q learning. The fact that MAXQ learns a representation of the
value function has an important benefit: it makes it possible to compute and
execute an improved, non-hierarchical policy via a procedure similar to the
policy improvement step of policy iteration. The paper demonstrates the
effectiveness of this non-hierarchical execution experimentally. Finally, the
paper concludes with a comparison to related work and a discussion of the
design tradeoffs in hierarchical reinforcement learning.
|
cs/9905015
|
State Abstraction in MAXQ Hierarchical Reinforcement Learning
|
cs.LG
|
Many researchers have explored methods for hierarchical reinforcement
learning (RL) with temporal abstractions, in which abstract actions are defined
that can perform many primitive actions before terminating. However, little is
known about learning with state abstractions, in which aspects of the state
space are ignored. In previous work, we developed the MAXQ method for
hierarchical RL. In this paper, we define five conditions under which state
abstraction can be combined with the MAXQ value function decomposition. We
prove that the MAXQ-Q learning algorithm converges under these conditions and
show experimentally that state abstraction is important for the successful
application of MAXQ-Q learning.
|
cs/9905016
|
Programs with Stringent Performance Objectives Will Often Exhibit
Chaotic Behavior
|
cs.CE cs.CC
|
Software for the resolution of certain kind of problems, those that rate high
in the Stringent Performance Objectives adjustment factor (IFPUG scheme), can
be described using a combination of game theory and autonomous systems. From
this description it can be shown that some of those problems exhibit chaotic
behavior, an important fact in understanding the functioning of the related
software. As a relatively simple example, it is shown that chess exhibits
chaotic behavior in its configuration space. This implies that static
evaluators in chess programs have intrinsic limitations.
|
cs/9906001
|
On Bounded-Weight Error-Correcting Codes
|
cs.IT math.IT
|
This paper computationally obtains optimal bounded-weight, binary,
error-correcting codes for a variety of distance bounds and dimensions. We
compare the sizes of our codes to the sizes of optimal constant-weight, binary,
error-correcting codes, and evaluate the differences.
|
cs/9906002
|
The Symbol Grounding Problem
|
cs.AI
|
How can the semantic interpretation of a formal symbol system be made
intrinsic to the system, rather than just parasitic on the meanings in our
heads? How can the meanings of the meaningless symbol tokens, manipulated
solely on the basis of their (arbitrary) shapes, be grounded in anything but
other meaningless symbols? The problem is analogous to trying to learn Chinese
from a Chinese/Chinese dictionary alone. A candidate solution is sketched:
Symbolic representations must be grounded bottom-up in nonsymbolic
representations of two kinds: (1) "iconic representations," which are analogs
of the proximal sensory projections of distal objects and events, and (2)
"categorical representations," which are learned and innate feature-detectors
that pick out the invariant features of object and event categories from their
sensory projections. Elementary symbols are the names of these object and event
categories, assigned on the basis of their (nonsymbolic) categorical
representations. Higher-order (3) "symbolic representations," grounded in these
elementary symbols, consist of symbol strings describing category membership
relations (e.g., "An X is a Y that is Z").
|
cs/9906003
|
The syntactic processing of particles in Japanese spoken language
|
cs.CL
|
Particles fullfill several distinct central roles in the Japanese language.
They can mark arguments as well as adjuncts, can be functional or have semantic
funtions. There is, however, no straightforward matching from particles to
functions, as, e.g., GA can mark the subject, the object or an adjunct of a
sentence. Particles can cooccur. Verbal arguments that could be identified by
particles can be eliminated in the Japanese sentence. And finally, in spoken
language particles are often omitted. A proper treatment of particles is thus
necessary to make an analysis of Japanese sentences possible. Our treatment is
based on an empirical investigation of 800 dialogues. We set up a type
hierarchy of particles motivated by their subcategorizational and
modificational behaviour. This type hierarchy is part of the Japanese syntax in
VERBMOBIL.
|
cs/9906004
|
Cascaded Grammatical Relation Assignment
|
cs.CL cs.LG
|
In this paper we discuss cascaded Memory-Based grammatical relations
assignment. In the first stages of the cascade, we find chunks of several types
(NP,VP,ADJP,ADVP,PP) and label them with their adverbial function (e.g. local,
temporal). In the last stage, we assign grammatical relations to pairs of
chunks. We studied the effect of adding several levels to this cascaded
classifier and we found that even the less performing chunkers enhanced the
performance of the relation finder.
|
cs/9906005
|
Memory-Based Shallow Parsing
|
cs.CL cs.LG
|
We present a memory-based learning (MBL) approach to shallow parsing in which
POS tagging, chunking, and identification of syntactic relations are formulated
as memory-based modules. The experiments reported in this paper show
competitive results, the F-value for the Wall Street Journal (WSJ) treebank is:
93.8% for NP chunking, 94.7% for VP chunking, 77.1% for subject detection and
79.0% for object detection.
|
cs/9906006
|
Learning Efficient Disambiguation
|
cs.CL cs.AI
|
This dissertation analyses the computational properties of current
performance-models of natural language parsing, in particular Data Oriented
Parsing (DOP), points out some of their major shortcomings and suggests
suitable solutions. It provides proofs that various problems of probabilistic
disambiguation are NP-Complete under instances of these performance-models, and
it argues that none of these models accounts for attractive efficiency
properties of human language processing in limited domains, e.g. that frequent
inputs are usually processed faster than infrequent ones. The central
hypothesis of this dissertation is that these shortcomings can be eliminated by
specializing the performance-models to the limited domains. The dissertation
addresses "grammar and model specialization" and presents a new framework, the
Ambiguity-Reduction Specialization (ARS) framework, that formulates the
necessary and sufficient conditions for successful specialization. The
framework is instantiated into specialization algorithms and applied to
specializing DOP. Novelties of these learning algorithms are 1) they limit the
hypotheses-space to include only "safe" models, 2) are expressed as constrained
optimization formulae that minimize the entropy of the training tree-bank given
the specialized grammar, under the constraint that the size of the specialized
model does not exceed a predefined maximum, and 3) they enable integrating the
specialized model with the original one in a complementary manner. The
dissertation provides experiments with initial implementations and compares the
resulting Specialized DOP (SDOP) models to the original DOP models with
encouraging results.
|
cs/9906009
|
Cascaded Markov Models
|
cs.CL
|
This paper presents a new approach to partial parsing of context-free
structures. The approach is based on Markov Models. Each layer of the resulting
structure is represented by its own Markov Model, and output of a lower layer
is passed as input to the next higher layer. An empirical evaluation of the
method yields very good results for NP/PP chunking of German newspaper texts.
|
cs/9906010
|
Predicate Logic with Definitions
|
cs.LO cs.AI
|
Predicate Logic with Definitions (PLD or D-logic) is a modification of
first-order logic intended mostly for practical formalization of mathematics.
The main syntactic constructs of D-logic are terms, formulas and definitions. A
definition is a definition of variables, a definition of constants, or a
composite definition (D-logic has also abbreviation definitions called
abbreviations). Definitions can be used inside terms and formulas. This
possibility alleviates introducing new quantifier-like names. Composite
definitions allow constructing new definitions from existing ones.
|
cs/9906011
|
A Newton method without evaluation of nonlinear function values
|
cs.CE cs.NA math.NA
|
The present author recently proposed and proved a relationship theorem
between nonlinear polynomial equations and the corresponding Jacobian matrix.
By using this theorem, this paper derives a Newton iterative formula without
requiring the evaluation of nonlinear function values in the solution of
nonlinear polynomial-only problems.
|
cs/9906012
|
The application of special matrix product to differential quadrature
solution of geometrically nonlinear bending of orthotropic rectangular plates
|
cs.CE cs.NA math.NA
|
The Hadamard and SJT product of matrices are two types of special matrix
product. The latter was first defined by Chen. In this study, they are applied
to the differential quadrature (DQ) solution of geometrically nonlinear bending
of isotropic and orthotropic rectangular plates. By using the Hadamard product,
the nonlinear formulations are greatly simplified, while the SJT product
approach minimizes the effort to evaluate the Jacobian derivative matrix in the
Newton-Raphson method for solving the resultant nonlinear formulations. In
addition, the coupled nonlinear formulations for the present problems can
easily be decoupled by means of the Hadamard and SJT product. Therefore, the
size of the simultaneous nonlinear algebraic equations is reduced by two-thirds
and the computing effort and storage requirements are alleviated greatly. Two
recent approaches applying the multiple boundary conditions are employed in the
present DQ nonlinear computations. The solution accuracies are improved
obviously in comparison to the previously given by Bert et al. The numerical
results and detailed solution procedures are provided to demonstrate the superb
efficiency, accuracy and simplicity of the new approaches in applying DQ method
for nonlinear computations.
|
cs/9906014
|
Evaluation of the NLP Components of the OVIS2 Spoken Dialogue System
|
cs.CL
|
The NWO Priority Programme Language and Speech Technology is a 5-year
research programme aiming at the development of spoken language information
systems. In the Programme, two alternative natural language processing (NLP)
modules are developed in parallel: a grammar-based (conventional, rule-based)
module and a data-oriented (memory-based, stochastic, DOP) module. In order to
compare the NLP modules, a formal evaluation has been carried out three years
after the start of the Programme. This paper describes the evaluation procedure
and the evaluation results. The grammar-based component performs much better
than the data-oriented one in this comparison.
|
cs/9906015
|
Learning Transformation Rules to Find Grammatical Relations
|
cs.CL
|
Grammatical relationships are an important level of natural language
processing. We present a trainable approach to find these relationships through
transformation sequences and error-driven learning. Our approach finds
grammatical relationships between core syntax groups and bypasses much of the
parsing phase. On our training and test set, our procedure achieves 63.6%
recall and 77.3% precision (f-score = 69.8).
|
cs/9906016
|
Automatically Selecting Useful Phrases for Dialogue Act Tagging
|
cs.AI cs.LG
|
We present an empirical investigation of various ways to automatically
identify phrases in a tagged corpus that are useful for dialogue act tagging.
We found that a new method (which measures a phrase's deviation from an
optimally-predictive phrase), enhanced with a lexical filtering mechanism,
produces significantly better cues than manually-selected cue phrases, the
exhaustive set of phrases in a training corpus, and phrases chosen by
traditional metrics, like mutual information and information gain.
|
cs/9906019
|
Resolving Part-of-Speech Ambiguity in the Greek Language Using Learning
Techniques
|
cs.CL cs.AI
|
This article investigates the use of Transformation-Based Error-Driven
learning for resolving part-of-speech ambiguity in the Greek language. The aim
is not only to study the performance, but also to examine its dependence on
different thematic domains. Results are presented here for two different test
cases: a corpus on "management succession events" and a general-theme corpus.
The two experiments show that the performance of this method does not depend on
the thematic domain of the corpus, and its accuracy for the Greek language is
around 95%.
|
cs/9906020
|
Temporal Meaning Representations in a Natural Language Front-End
|
cs.CL
|
Previous work in the context of natural language querying of temporal
databases has established a method to map automatically from a large subset of
English time-related questions to suitable expressions of a temporal logic-like
language, called TOP. An algorithm to translate from TOP to the TSQL2 temporal
database language has also been defined. This paper shows how TOP expressions
could be translated into a simpler logic-like language, called BOT. BOT is very
close to traditional first-order predicate logic (FOPL), and hence existing
methods to manipulate FOPL expressions can be exploited to interface to
time-sensitive applications other than TSQL2 databases, maintaining the
existing English-to-TOP mapping.
|
cs/9906025
|
Mapping Multilingual Hierarchies Using Relaxation Labeling
|
cs.CL
|
This paper explores the automatic construction of a multilingual Lexical
Knowledge Base from pre-existing lexical resources. We present a new and robust
approach for linking already existing lexical/semantic hierarchies. We used a
constraint satisfaction algorithm (relaxation labeling) to select --among all
the candidate translations proposed by a bilingual dictionary-- the right
English WordNet synset for each sense in a taxonomy automatically derived from
a Spanish monolingual dictionary. Although on average, there are 15 possible
WordNet connections for each sense in the taxonomy, the method achieves an
accuracy over 80%. Finally, we also propose several ways in which this
technique could be applied to enrich and improve existing lexical databases.
|
cs/9906026
|
Robust Grammatical Analysis for Spoken Dialogue Systems
|
cs.CL
|
We argue that grammatical analysis is a viable alternative to concept
spotting for processing spoken input in a practical spoken dialogue system. We
discuss the structure of the grammar, and a model for robust parsing which
combines linguistic sources of information and statistical sources of
information. We discuss test results suggesting that grammatical processing
allows fast and accurate processing of spoken input.
|
cs/9906027
|
Human-Computer Conversation
|
cs.CL cs.HC
|
The article surveys a little of the history of the technology, sets out the
main current theoretical approaches in brief, and discusses the on-going
opposition between theoretical and empirical approaches. It illustrates the
situation with some discussion of CONVERSE, a system that won the Loebner prize
in 1997 and which displays features of both approaches.
|
cs/9906029
|
Events in Property Patterns
|
cs.SE cs.AI cs.CL cs.SC
|
A pattern-based approach to the presentation, codification and reuse of
property specifications for finite-state verification was proposed by Dwyer and
his collegues. The patterns enable non-experts to read and write formal
specifications for realistic systems and facilitate easy conversion of
specifications between formalisms, such as LTL, CTL, QRE. In this paper, we
extend the pattern system with events - changes of values of variables in the
context of LTL.
|
cs/9906034
|
A Unified Example-Based and Lexicalist Approach to Machine Translation
|
cs.CL
|
We present an approach to Machine Translation that combines the ideas and
methodologies of the Example-Based and Lexicalist theoretical frameworks. The
approach has been implemented in a multilingual Machine Translation system.
|
cs/9907003
|
Annotation graphs as a framework for multidimensional linguistic data
analysis
|
cs.CL
|
In recent work we have presented a formal framework for linguistic annotation
based on labeled acyclic digraphs. These `annotation graphs' offer a simple yet
powerful method for representing complex annotation structures incorporating
hierarchy and overlap. Here, we motivate and illustrate our approach using
discourse-level annotations of text and speech data drawn from the CALLHOME,
COCONUT, MUC-7, DAMSL and TRAINS annotation schemes. With the help of domain
specialists, we have constructed a hybrid multi-level annotation for a fragment
of the Boston University Radio Speech Corpus which includes the following
levels: segment, word, breath, ToBI, Tilt, Treebank, coreference and named
entity. We show how annotation graphs can represent hybrid multi-level
structures which derive from a diverse set of file formats. We also show how
the approach facilitates substantive comparison of multiple annotations of a
single signal based on different theoretical models. The discussion shows how
annotation graphs open the door to wide-ranging integration of tools, formats
and corpora.
|
cs/9907004
|
MAP Lexicon is useful for segmentation and word discovery in
child-directed speech
|
cs.CL cs.LG
|
Because of rather fundamental changes to the underlying model proposed in the
paper, it has been withdrawn from the archive.
|
cs/9907006
|
Representing Text Chunks
|
cs.CL
|
Dividing sentences in chunks of words is a useful preprocessing step for
parsing, information extraction and information retrieval. (Ramshaw and Marcus,
1995) have introduced a "convenient" data representation for chunking by
converting it to a tagging task. In this paper we will examine seven different
data representations for the problem of recognizing noun phrase chunks. We will
show that the the data representation choice has a minor influence on chunking
performance. However, equipped with the most suitable data representation, our
memory-based learning chunker was able to improve the best published chunking
results for a standard data set.
|
cs/9907007
|
Cross-Language Information Retrieval for Technical Documents
|
cs.CL
|
This paper proposes a Japanese/English cross-language information retrieval
(CLIR) system targeting technical documents. Our system first translates a
given query containing technical terms into the target language, and then
retrieves documents relevant to the translated query. The translation of
technical terms is still problematic in that technical terms are often compound
words, and thus new terms can be progressively created simply by combining
existing base words. In addition, Japanese often represents loanwords based on
its phonogram. Consequently, existing dictionaries find it difficult to achieve
sufficient coverage. To counter the first problem, we use a compound word
translation method, which uses a bilingual dictionary for base words and
collocational statistics to resolve translation ambiguity. For the second
problem, we propose a transliteration method, which identifies phonetic
equivalents in the target language. We also show the effectiveness of our
system using a test collection for CLIR.
|
cs/9907008
|
Explanation-based Learning for Machine Translation
|
cs.CL
|
In this paper we present an application of explanation-based learning (EBL)
in the parsing module of a real-time English-Spanish machine translation system
designed to translate closed captions. We discuss the efficiency/coverage
trade-offs available in EBL and introduce the techniques we use to increase
coverage while maintaining a high level of space and time efficiency. Our
performance results indicate that this approach is effective.
|
cs/9907009
|
Designing and Mining Multi-Terabyte Astronomy Archives: The Sloan
Digital Sky Survey
|
cs.DB cs.DL
|
The next-generation astronomy digital archives will cover most of the
universe at fine resolution in many wave-lengths, from X-rays to ultraviolet,
optical, and infrared. The archives will be stored at diverse geographical
locations. One of the first of these projects, the Sloan Digital Sky Survey
(SDSS) will create a 5-wavelength catalog over 10,000 square degrees of the sky
(see http://www.sdss.org/). The 200 million objects in the multi-terabyte
database will have mostly numerical attributes, defining a space of 100+
dimensions. Points in this space have highly correlated distributions.
The archive will enable astronomers to explore the data interactively. Data
access will be aided by a multidimensional spatial index and other indices. The
data will be partitioned in many ways. Small tag objects consisting of the most
popular attributes speed up frequent searches. Splitting the data among
multiple servers enables parallel, scalable I/O and applies parallel processing
to the data. Hashing techniques allow efficient clustering and pair-wise
comparison algorithms that parallelize nicely. Randomly sampled subsets allow
debugging otherwise large queries at the desktop. Central servers will operate
a data pump that supports sweeping searches that touch most of the data. The
anticipated queries require special operators related to angular distances and
complex similarity tests of object properties, like shapes, colors, velocity
vectors, or temporal behaviors. These issues pose interesting data management
challenges.
|
cs/9907010
|
Language Identification With Confidence Limits
|
cs.CL
|
A statistical classification algorithm and its application to language
identification from noisy input are described. The main innovation is to
compute confidence limits on the classification, so that the algorithm
terminates when enough evidence to make a clear decision has been made, and so
avoiding problems with categories that have similar characteristics. A second
application, to genre identification, is briefly examined. The results show
that some of the problems of other language identification techniques can be
avoided, and illustrate a more important point: that a statistical language
process can be used to provide feedback about its own success rate.
|
cs/9907012
|
Selective Magic HPSG Parsing
|
cs.CL
|
We propose a parser for constraint-logic grammars implementing HPSG that
combines the advantages of dynamic bottom-up and advanced top-down control. The
parser allows the user to apply magic compilation to specific constraints in a
grammar which as a result can be processed dynamically in a bottom-up and
goal-directed fashion. State of the art top-down processing techniques are used
to deal with the remaining constraints. We discuss various aspects concerning
the implementation of the parser as part of a grammar development system.
|
cs/9907013
|
Corpus Annotation for Parser Evaluation
|
cs.CL
|
We describe a recently developed corpus annotation scheme for evaluating
parsers that avoids shortcomings of current methods. The scheme encodes
grammatical relations between heads and dependents, and has been used to mark
up a new public-domain corpus of naturally occurring English text. We show how
the corpus can be used to evaluate the accuracy of a robust parser, and relate
the corpus to extant resources.
|
cs/9907016
|
Microsoft TerraServer: A Spatial Data Warehouse
|
cs.DB cs.DL
|
The TerraServer stores aerial, satellite, and topographic images of the earth
in a SQL database available via the Internet. It is the world's largest online
atlas, combining five terabytes of image data from the United States Geological
Survey (USGS) and SPIN-2. This report describes the system-redesign based on
our experience over the last year. It also reports usage and operations results
over the last year -- over 2 billion web hits and over 20 Terabytes of imagry
served over the Internet. Internet browsers provide intuitive spatial and text
interfaces to the data. Users need no special hardware, software, or knowledge
to locate and browse imagery. This paper describes how terabytes of "Internet
unfriendly" geo-spatial images were scrubbed and edited into hundreds of
millions of "Internet friendly" image tiles and loaded into a SQL data
warehouse. Microsoft TerraServer demonstrates that general-purpose relational
database technology can manage large scale image repositories, and shows that
web browsers can be a good geospatial image presentation system.
|
cs/9907017
|
A Bootstrap Approach to Automatically Generating Lexical Transfer Rules
|
cs.CL
|
We describe a method for automatically generating Lexical Transfer Rules
(LTRs) from word equivalences using transfer rule templates. Templates are
skeletal LTRs, unspecified for words. New LTRs are created by instantiating a
template with words, provided that the words belong to the appropriate lexical
categories required by the template. We define two methods for creating an
inventory of templates and using them to generate new LTRs. A simpler method
consists of extracting a finite set of templates from a sample of hand coded
LTRs and directly using them in the generation process. A further method
consists of abstracting over the initial finite set of templates to define
higher level templates, where bilingual equivalences are defined in terms of
correspondences involving phrasal categories. Phrasal templates are then mapped
onto sets of lexical templates with the aid of grammars. In this way an
infinite set of lexical templates is recursively defined. New LTRs are created
by parsing input words, matching a template at the phrasal level and using the
corresponding lexical categories to instantiate the lexical template. The
definition of an infinite set of templates enables the automatic creation of
LTRs for multi-word, non-compositional word equivalences of any cardinality.
|
cs/9907020
|
Generalized linearization in nonlinear modeling of data
|
cs.CE cs.NA math.NA
|
The principal innovative idea in this paper is to transform the original
complex nonlinear modeling problem into a combination of linear problem and
very simple nonlinear problems. The key step is the generalized linearization
of nonlinear terms. This paper only presents the introductory strategy of this
methodology. The practical numerical experiments will be provided subsequently.
|
cs/9907021
|
Architectural Considerations for Conversational Systems -- The
Verbmobil/INTARC Experience
|
cs.CL
|
The paper describes the speech to speech translation system INTARC, developed
during the first phase of the Verbmobil project. The general design goals of
the INTARC system architecture were time synchronous processing as well as
incrementality and interactivity as a means to achieve a higher degree of
robustness and scalability. Interactivity means that in addition to the
bottom-up (in terms of processing levels) data flow the ability to process
top-down restrictions considering the same signal segment for all processing
levels. The construction of INTARC 2.0, which has been operational since fall
1996, followed an engineering approach focussing on the integration of symbolic
(linguistic) and stochastic (recognition) techniques which led to a
generalization of the concept of a ``one pass'' beam search.
|
cs/9907026
|
Mixing representation levels: The hybrid approach to automatic text
generation
|
cs.CL cs.AI
|
Natural language generation systems (NLG) map non-linguistic representations
into strings of words through a number of steps using intermediate
representations of various levels of abstraction. Template based systems, by
contrast, tend to use only one representation level, i.e. fixed strings, which
are combined, possibly in a sophisticated way, to generate the final text.
In some circumstances, it may be profitable to combine NLG and template based
techniques. The issue of combining generation techniques can be seen in more
abstract terms as the issue of mixing levels of representation of different
degrees of linguistic abstraction. This paper aims at defining a reference
architecture for systems using mixed representations. We argue that mixed
representations can be used without abandoning a linguistically grounded
approach to language generation.
|
cs/9907032
|
Clausal Temporal Resolution
|
cs.LO cs.AI
|
In this article, we examine how clausal resolution can be applied to a
specific, but widely used, non-classical logic, namely discrete linear temporal
logic. Thus, we first define a normal form for temporal formulae and show how
arbitrary temporal formulae can be translated into the normal form, while
preserving satisfiability. We then introduce novel resolution rules that can be
applied to formulae in this normal form, provide a range of examples and
examine the correctness and complexity of this approach is examined and. This
clausal resolution approach. Finally, we describe related work and future
developments concerning this work.
|
cs/9907042
|
Raising Reliability of Web Search Tool Research through Replication and
Chaos Theory
|
cs.IR cs.DL
|
Because the World Wide Web is a dynamic collection of information, the Web
search tools (or "search engines") that index the Web are dynamic. Traditional
information retrieval evaluation techniques may not provide reliable results
when applied to the Web search tools. This study is the result of ten
replications of the classic 1996 Ding and Marchionini Web search tool research.
It explores the effects that replication can have on transforming unreliable
results from one iteration into replicable and therefore reliable results after
multiple iterations.
|
cs/9907043
|
A simple C++ library for manipulating scientific data sets as structured
data
|
cs.CE cs.DB
|
Representing scientific data sets efficiently on external storage usually
involves converting them to a byte string representation using specialized
reader/writer routines. The resulting storage files are frequently difficult to
interpret without these specialized routines as they do not contain information
about the logical structure of the data. Avoiding such problems usually
involves heavy-weight data format libraries or data base systems. We present a
simple C++ library that allows to create and access data files that store
structured data. The structure of the data is described by a data type that can
be built from elementary data types (integer and floating-point numbers, byte
strings) and composite data types (arrays, structures, unions). An abstract
data access class presents the data to the application. Different actual data
file structures can be implemented under this layer. This method is
particularly suited to applications that require complex data structures, e.g.
molecular dynamics simulations. Extensions such as late type binding and object
persistence are discussed.
|
cs/9908001
|
Detecting Sub-Topic Correspondence through Bipartite Term Clustering
|
cs.CL
|
This paper addresses a novel task of detecting sub-topic correspondence in a
pair of text fragments, enhancing common notions of text similarity. This task
is addressed by coupling corresponding term subsets through bipartite
clustering. The paper presents a cost-based clustering scheme and compares it
with a bipartite version of the single-link method, providing illustrating
results.
|
cs/9908004
|
Extending the Stable Model Semantics with More Expressive Rules
|
cs.LO cs.AI
|
The rules associated with propositional logic programs and the stable model
semantics are not expressive enough to let one write concise programs. This
problem is alleviated by introducing some new types of propositional rules.
Together with a decision procedure that has been used as a base for an
efficient implementation, the new rules supplant the standard ones in practical
applications of the stable model semantics.
|
cs/9908013
|
Collective Intelligence for Control of Distributed Dynamical Systems
|
cs.LG adap-org cond-mat cs.AI cs.DC cs.MA nlin.AO
|
We consider the El Farol bar problem, also known as the minority game (W. B.
Arthur, ``The American Economic Review'', 84(2): 406--411 (1994), D. Challet
and Y.C. Zhang, ``Physica A'', 256:514 (1998)). We view it as an instance of
the general problem of how to configure the nodal elements of a distributed
dynamical system so that they do not ``work at cross purposes'', in that their
collective dynamics avoids frustration and thereby achieves a provided global
goal. We summarize a mathematical theory for such configuration applicable when
(as in the bar problem) the global goal can be expressed as minimizing a global
energy function and the nodes can be expressed as minimizers of local free
energy functions. We show that a system designed with that theory performs
nearly optimally for the bar problem.
|
cs/9908014
|
An Introduction to Collective Intelligence
|
cs.LG adap-org cond-mat cs.DC cs.MA nlin.AO
|
This paper surveys the emerging science of how to design a ``COllective
INtelligence'' (COIN). A COIN is a large multi-agent system where:
(i) There is little to no centralized communication or control; and
(ii) There is a provided world utility function that rates the possible
histories of the full system.
In particular, we are interested in COINs in which each agent runs a
reinforcement learning (RL) algorithm. Rather than use a conventional modeling
approach (e.g., model the system dynamics, and hand-tune agents to cooperate),
we aim to solve the COIN design problem implicitly, via the ``adaptive''
character of the RL algorithms of each of the agents. This approach introduces
an entirely new, profound design problem: Assuming the RL algorithms are able
to achieve high rewards, what reward functions for the individual agents will,
when pursued by those agents, result in high world utility? In other words,
what reward functions will best ensure that we do not have phenomena like the
tragedy of the commons, Braess's paradox, or the liquidity trap?
Although still very young, research specifically concentrating on the COIN
design problem has already resulted in successes in artificial domains, in
particular in packet-routing, the leader-follower problem, and in variants of
Arthur's El Farol bar problem. It is expected that as it matures and draws upon
other disciplines related to COINs, this research will greatly expand the range
of tasks addressable by human engineers. Moreover, in addition to drawing on
them, such a fully developed scie nce of COIN design may provide much insight
into other already established scientific fields, such as economics, game
theory, and population biology.
|
cs/9908015
|
Representing Scholarly Claims in Internet Digital Libraries: A Knowledge
Modelling Approach
|
cs.DL cs.AI cs.HC cs.IR
|
This paper is concerned with tracking and interpreting scholarly documents in
distributed research communities. We argue that current approaches to document
description, and current technological infrastructures particularly over the
World Wide Web, provide poor support for these tasks. We describe the design of
a digital library server which will enable authors to submit a summary of the
contributions they claim their documents makes, and its relations to the
literature. We describe a knowledge-based Web environment to support the
emergence of such a community-constructed semantic hypertext, and the services
it could provide to assist the interpretation of an idea or document in the
context of its literature. The discussion considers in detail how the approach
addresses usability issues associated with knowledge structuring environments.
|
cs/9908017
|
A Differential Invariant for Zooming
|
cs.CV
|
This paper presents an invariant under scaling and linear brightness change.
The invariant is based on differentials and therefore is a local feature.
Rotationally invariant 2-d differential Gaussian operators up to third order
are proposed for the implementation of the invariant. The performance is
analyzed by simulating a camera zoom-out.
|
cs/9909002
|
Semantic robust parsing for noun extraction from natural language
queries
|
cs.CL
|
This paper describes how robust parsing techniques can be fruitful applied
for building a query generation module which is part of a pipelined NLP
architecture aimed at process natural language queries in a restricted domain.
We want to show that semantic robustness represents a key issue in those NLP
systems where it is more likely to have partial and ill-formed utterances due
to various factors (e.g. noisy environments, low quality of speech recognition
modules, etc...) and where it is necessary to succeed, even if partially, in
extracting some meaningful information.
|
cs/9909003
|
Iterative Deepening Branch and Bound
|
cs.AI
|
In tree search problem the best-first search algorithm needs too much of
space . To remove such drawbacks of these algorithms the IDA* was developed
which is both space and time cost efficient. But again IDA* can give an optimal
solution for real valued problems like Flow shop scheduling, Travelling
Salesman and 0/1 Knapsack due to their real valued cost estimates. Thus further
modifications are done on it and the Iterative Deepening Branch and Bound
Search Algorithms is developed which meets the requirements. We have tried
using this algorithm for the Flow Shop Scheduling Problem and have found that
it is quite effective.
|
cs/9909009
|
The Rough Guide to Constraint Propagation
|
cs.AI cs.PL
|
We provide here a simple, yet very general framework that allows us to
explain several constraint propagation algorithms in a systematic way. In
particular, using the notions commutativity and semi-commutativity, we show how
the well-known AC-3, PC-2, DAC and DPC algorithms are instances of a single
generic algorithm. The work reported here extends and simplifies that of Apt,
cs.AI/9811024.
|
cs/9909010
|
Automatic Generation of Constraint Propagation Algorithms for Small
Finite Domains
|
cs.AI cs.PL
|
We study here constraint satisfaction problems that are based on predefined,
explicitly given finite constraints. To solve them we propose a notion of rule
consistency that can be expressed in terms of rules derived from the explicit
representation of the initial constraints.
This notion of local consistency is weaker than arc consistency for
constraints of arbitrary arity but coincides with it when all domains are unary
or binary. For Boolean constraints rule consistency coincides with the closure
under the well-known propagation rules for Boolean constraints.
By generalizing the format of the rules we obtain a characterization of arc
consistency in terms of so-called inclusion rules. The advantage of rule
consistency and this rule based characterization of the arc consistency is that
the algorithms that enforce both notions can be automatically generated, as CHR
rules. So these algorithms could be integrated into constraint logic
programming systems such as Eclipse.
We illustrate the usefulness of this approach to constraint propagation by
discussing the implementations of both algorithms and their use on various
examples, including Boolean constraints, three valued logic of Kleene,
constraints dealing with Waltz's language for describing polyhedreal scenes,
and Allen's qualitative approach to temporal logic.
|
cs/9909014
|
Reasoning About Common Knowledge with Infinitely Many Agents
|
cs.LO cs.AI
|
Complete axiomatizations and exponential-time decision procedures are
provided for reasoning about knowledge and common knowledge when there are
infinitely many agents. The results show that reasoning about knowledge and
common knowledge with infinitely many agents is no harder than when there are
finitely many agents, provided that we can check the cardinality of certain set
differences G - G', where G and G' are sets of agents. Since our complexity
results are independent of the cardinality of the sets G involved, they
represent improvements over the previous results even with the sets of agents
involved are finite. Moreover, our results make clear the extent to which
issues of complexity and completeness depend on how the sets of agents involved
are represented.
|
cs/9909016
|
Least expected cost query optimization: an exercise in utility
|
cs.DB
|
We identify two unreasonable, though standard, assumptions made by database
query optimizers that can adversely affect the quality of the chosen evaluation
plans. One assumption is that it is enough to optimize for the expected
case---that is, the case where various parameters (like available memory) take
on their expected value. The other assumption is that the parameters are
constant throughout the execution of the query. We present an algorithm based
on the ``System R''-style query optimization algorithm that does not rely on
these assumptions. The algorithm we present chooses the plan of the least
expected cost instead of the plan of least cost given some fixed value of the
parameters. In execution environments that exhibit a high degree of
variability, our techniques should result in better performance.
|
cs/9909019
|
Knowledge in Multi-Agent Systems: Initial Configurations and Broadcast
|
cs.LO cs.AI
|
The semantic framework for the modal logic of knowledge due to Halpern and
Moses provides a way to ascribe knowledge to agents in distributed and
multi-agent systems. In this paper we study two special cases of this
framework: full systems and hypercubes. Both model static situations in which
no agent has any information about another agent's state. Full systems and
hypercubes are an appropriate model for the initial configurations of many
systems of interest. We establish a correspondence between full systems and
hypercube systems and certain classes of Kripke frames. We show that these
classes of systems correspond to the same logic. Moreover, this logic is also
the same as that generated by the larger class of weakly directed frames. We
provide a sound and complete axiomatization, S5WDn, of this logic. Finally, we
show that under certain natural assumptions, in a model where knowledge evolves
over time, S5WDn characterizes the properties of knowledge not just at the
initial configuration, but also at all later configurations. In particular,
this holds for homogeneous broadcast systems, which capture settings in which
agents are initially ignorant of each others local states, operate
synchronously, have perfect recall and can communicate only by broadcasting.
|
cs/9910011
|
A statistical model for word discovery in child directed speech
|
cs.CL cs.LG
|
A statistical model for segmentation and word discovery in child directed
speech is presented. An incremental unsupervised learning algorithm to infer
word boundaries based on this model is described and results of empirical tests
showing that the algorithm is competitive with other models that have been used
for similar tasks are also presented.
|
cs/9910015
|
PIPE: Personalizing Recommendations via Partial Evaluation
|
cs.IR cs.AI
|
It is shown that personalization of web content can be advantageously viewed
as a form of partial evaluation --- a technique well known in the programming
languages community. The basic idea is to model a recommendation space as a
program, then partially evaluate this program with respect to user preferences
(and features) to obtain specialized content. This technique supports both
content-based and collaborative approaches, and is applicable to a range of
applications that require automatic information integration from multiple web
sources. The effectiveness of this methodology is illustrated by two example
applications --- (i) personalizing content for visitors to the Blacksburg
Electronic Village (http://www.bev.net), and (ii) locating and selecting
scientific software on the Internet. The scalability of this technique is
demonstrated by its ability to interface with online web ontologies that index
thousands of web pages.
|
cs/9910016
|
Probabilistic Agent Programs
|
cs.AI
|
Agents are small programs that autonomously take actions based on changes in
their environment or ``state.'' Over the last few years, there have been an
increasing number of efforts to build agents that can interact and/or
collaborate with other agents. In one of these efforts, Eiter, Subrahmanian amd
Pick (AIJ, 108(1-2), pages 179-255) have shown how agents may be built on top
of legacy code. However, their framework assumes that agent states are
completely determined, and there is no uncertainty in an agent's state. Thus,
their framework allows an agent developer to specify how his agents will react
when the agent is 100% sure about what is true/false in the world state. In
this paper, we propose the concept of a \emph{probabilistic agent program} and
show how, given an arbitrary program written in any imperative language, we may
build a declarative ``probabilistic'' agent program on top of it which supports
decision making in the presence of uncertainty. We provide two alternative
semantics for probabilistic agent programs. We show that the second semantics,
though more epistemically appealing, is more complex to compute. We provide
sound and complete algorithms to compute the semantics of \emph{positive} agent
programs.
|
cs/9910019
|
Consistent Checkpointing in Distributed Databases: Towards a Formal
Approach
|
cs.DB cs.DC
|
Whether it is for audit or for recovery purposes, data checkpointing is an
important problem of distributed database systems. Actually, transactions
establish dependence relations on data checkpoints taken by data object
managers. So, given an arbitrary set of data checkpoints (including at least a
single data checkpoint from a data manager, and at most a data checkpoint from
each data manager), an important question is the following one: ``Can these
data checkpoints be members of a same consistent global checkpoint?''. This
paper answers this question by providing a necessary and sufficient condition
suited for database systems. Moreover, to show the usefulness of this
condition, two {\em non-intrusive} data checkpointing protocols are derived
from this condition. It is also interesting to note that this paper, by
exhibiting ``correspondences'', establishes a bridge between the data
object/transaction model and the process/message-passing model.
|
cs/9910020
|
Selective Sampling for Example-based Word Sense Disambiguation
|
cs.CL
|
This paper proposes an efficient example sampling method for example-based
word sense disambiguation systems. To construct a database of practical size, a
considerable overhead for manual sense disambiguation (overhead for
supervision) is required. In addition, the time complexity of searching a
large-sized database poses a considerable problem (overhead for search). To
counter these problems, our method selectively samples a smaller-sized
effective subset from a given example set for use in word sense disambiguation.
Our method is characterized by the reliance on the notion of training utility:
the degree to which each example is informative for future example sampling
when used for the training of the system. The system progressively collects
examples by selecting those with greatest utility. The paper reports the
effectiveness of our method through experiments on about one thousand
sentences. Compared to experiments with other example sampling methods, our
method reduced both the overhead for supervision and the overhead for search,
without the degeneration of the performance of the system.
|
cs/9910021
|
Efficient and Extensible Algorithms for Multi Query Optimization
|
cs.DB
|
Complex queries are becoming commonplace, with the growing use of decision
support systems. These complex queries often have a lot of common
sub-expressions, either within a single query, or across multiple such queries
run as a batch. Multi-query optimization aims at exploiting common
sub-expressions to reduce evaluation cost. Multi-query optimization has
hither-to been viewed as impractical, since earlier algorithms were exhaustive,
and explore a doubly exponential search space.
In this paper we demonstrate that multi-query optimization using heuristics
is practical, and provides significant benefits. We propose three cost-based
heuristic algorithms: Volcano-SH and Volcano-RU, which are based on simple
modifications to the Volcano search strategy, and a greedy heuristic. Our
greedy heuristic incorporates novel optimizations that improve efficiency
greatly. Our algorithms are designed to be easily added to existing optimizers.
We present a performance study comparing the algorithms, using workloads
consisting of queries from the TPC-D benchmark. The study shows that our
algorithms provide significant benefits over traditional optimization, at a
very acceptable overhead in optimization time.
|
cs/9910022
|
Practical experiments with regular approximation of context-free
languages
|
cs.CL
|
Several methods are discussed that construct a finite automaton given a
context-free grammar, including both methods that lead to subsets and those
that lead to supersets of the original context-free language. Some of these
methods of regular approximation are new, and some others are presented here in
a more refined form with respect to existing literature. Practical experiments
with the different methods of regular approximation are performed for
spoken-language input: hypotheses from a speech recognizer are filtered through
a finite automaton.
|
cs/9911006
|
Question Answering System Using Syntactic Information
|
cs.CL
|
Question answering task is now being done in TREC8 using English documents.
We examined question answering task in Japanese sentences. Our method selects
the answer by matching the question sentence with knowledge-based data written
in natural language. We use syntactic information to obtain highly accurate
answers.
|
cs/9911011
|
One-Level Prosodic Morphology
|
cs.CL
|
Recent developments in theoretical linguistics have lead to a widespread
acceptance of constraint-based analyses of prosodic morphology phenomena such
as truncation, infixation, floating morphemes and reduplication. Of these,
reduplication 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 argue for certain extensions to the one-level model of phonology
and morphology (Bird & Ellison 1994) to cover the computational aspects of
prosodic morphology using finite-state methods. In a nutshell, enriched lexical
representations provide additional automaton arcs to repeat or skip sounds and
also to allow insertion of additional material. A kind of resource
consciousness is introduced to control this additional freedom, distinguishing
between producer and consumer arcs. The non-finite-state copying aspect of
reduplication is mapped to automata intersection, itself a non-finite-state
operation. Bounded local optimization prunes certain automaton arcs that fail
to contribute to linguistic optimisation criteria. The paper then presents
implemented case studies of Ulwa construct state infixation, German
hypocoristic truncation and Tagalog over-applying reduplication that illustrate
the expressive power of this approach, before its merits and limitations are
discussed and possible extensions are sketched. I conclude that the one-level
approach to prosodic morphology presents an attractive way of extending
finite-state techniques to difficult phenomena that hitherto resisted elegant
computational analyses.
|
cs/9911012
|
Cox's Theorem Revisited
|
cs.AI
|
The assumptions needed to prove Cox's Theorem are discussed and examined.
Various sets of assumptions under which a Cox-style theorem can be proved are
provided, although all are rather strong and, arguably, not natural.
|
cs/9912002
|
A Geometric Model for Information Retrieval Systems
|
cs.IR cs.CC cs.DL
|
This decade has seen a great deal of progress in the development of
information retrieval systems. Unfortunately, we still lack a systematic
understanding of the behavior of the systems and their relationship with
documents. In this paper we present a completely new approach towards the
understanding of the information retrieval systems. Recently, it has been
observed that retrieval systems in TREC 6 show some remarkable patterns in
retrieving relevant documents. Based on the TREC 6 observations, we introduce a
geometric linear model of information retrieval systems. We then apply the
model to predict the number of relevant documents by the retrieval systems. The
model is also scalable to a much larger data set. Although the model is
developed based on the TREC 6 routing test data, I believe it can be readily
applicable to other information retrieval systems. In Appendix, we explained a
simple and efficient way of making a better system from the existing systems.
|
cs/9912003
|
Resolution of Indirect Anaphora in Japanese Sentences Using Examples 'X
no Y (Y of X)'
|
cs.CL
|
A noun phrase can indirectly refer to an entity that has already been
mentioned. For example, ``I went into an old house last night. The roof was
leaking badly and ...'' indicates that ``the roof'' is associated with `` an
old house}'', which was mentioned in the previous sentence. This kind of
reference (indirect anaphora) has not been studied well in natural language
processing, but is important for coherence resolution, language understanding,
and machine translation. In order to analyze indirect anaphora, we need a case
frame dictionary for nouns that contains knowledge of the relationships between
two nouns but no such dictionary presently exists. Therefore, we are forced to
use examples of ``X no Y'' (Y of X) and a verb case frame dictionary instead.
We tried estimating indirect anaphora using this information and obtained a
recall rate of 63% and a precision rate of 68% on test sentences. This
indicates that the information of ``X no Y'' is useful to a certain extent when
we cannot make use of a noun case frame dictionary. We estimated the results
that would be given by a noun case frame dictionary, and obtained recall and
precision rates of 71% and 82% respectively. Finally, we proposed a way to
construct a noun case frame dictionary by using examples of ``X no Y.''
|
cs/9912004
|
Pronoun Resolution in Japanese Sentences Using Surface Expressions and
Examples
|
cs.CL
|
In this paper, we present a method of estimating referents of demonstrative
pronouns, personal pronouns, and zero pronouns in Japanese sentences using
examples, surface expressions, topics and foci. Unlike conventional work which
was semantic markers for semantic constraints, we used examples for semantic
constraints and showed in our experiments that examples are as useful as
semantic markers. We also propose many new methods for estimating referents of
pronouns. For example, we use the form ``X of Y'' for estimating referents of
demonstrative adjectives. In addition to our new methods, we used many
conventional methods. As a result, experiments using these methods obtained a
precision rate of 87% in estimating referents of demonstrative pronouns,
personal pronouns, and zero pronouns for training sentences, and obtained a
precision rate of 78% for test sentences.
|
cs/9912005
|
An Estimate of Referent of Noun Phrases in Japanese Sentences
|
cs.CL
|
In machine translation and man-machine dialogue, it is important to clarify
referents of noun phrases. We present a method for determining the referents of
noun phrases in Japanese sentences by using the referential properties,
modifiers, and possessors of noun phrases. Since the Japanese language has no
articles, it is difficult to decide whether a noun phrase has an antecedent or
not. We had previously estimated the referential properties of noun phrases
that correspond to articles by using clue words in the sentences. By using
these referential properties, our system determined the referents of noun
phrases in Japanese sentences. Furthermore we used the modifiers and possessors
of noun phrases in determining the referents of noun phrases. As a result, on
training sentences we obtained a precision rate of 82% and a recall rate of 85%
in the determination of the referents of noun phrases that have antecedents. On
test sentences, we obtained a precision rate of 79% and a recall rate of 77%.
|
cs/9912006
|
Resolution of Verb Ellipsis in Japanese Sentence using Surface
Expressions and Examples
|
cs.CL
|
Verbs are sometimes omitted in Japanese sentences. It is necessary to recover
omitted verbs for purposes of language understanding, machine translation, and
conversational processing. This paper describes a practical way to recover
omitted verbs by using surface expressions and examples. We experimented the
resolution of verb ellipses by using this information, and obtained a recall
rate of 73% and a precision rate of 66% on test sentences.
|
cs/9912007
|
An Example-Based Approach to Japanese-to-English Translation of Tense,
Aspect, and Modality
|
cs.CL
|
We have developed a new method for Japanese-to-English translation of tense,
aspect, and modality that uses an example-based method. In this method the
similarity between input and example sentences is defined as the degree of
semantic matching between the expressions at the ends of the sentences. Our
method also uses the k-nearest neighbor method in order to exclude the effects
of noise; for example, wrongly tagged data in the bilingual corpora.
Experiments show that our method can translate tenses, aspects, and modalities
more accurately than the top-level MT software currently available on the
market can. Moreover, it does not require hand-craft rules.
|
cs/9912008
|
New Error Bounds for Solomonoff Prediction
|
cs.AI cs.LG
|
Solomonoff sequence prediction is a scheme to predict digits of binary
strings without knowing the underlying probability distribution. We call a
prediction scheme informed when it knows the true probability distribution of
the sequence. Several new relations between universal Solomonoff sequence
prediction and informed prediction and general probabilistic prediction schemes
will be proved. Among others, they show that the number of errors in Solomonoff
prediction is finite for computable distributions, if finite in the informed
case. Deterministic variants will also be studied. The most interesting result
is that the deterministic variant of Solomonoff prediction is optimal compared
to any other probabilistic or deterministic prediction scheme apart from
additive square root corrections only. This makes it well suited even for
difficult prediction problems, where it does not suffice when the number of
errors is minimal to within some factor greater than one. Solomonoff's original
bound and the ones presented here complement each other in a useful way.
|
cs/9912009
|
Deduction over Mixed-Level Logic Representations for Text Passage
Retrieval
|
cs.CL
|
A system is described that uses a mixed-level representation of (part of)
meaning of natural language documents (based on standard Horn Clause Logic) and
a variable-depth search strategy that distinguishes between the different
levels of abstraction in the knowledge representation to locate specific
passages in the documents. Mixed-level representations as well as
variable-depth search strategies are applicable in fields outside that of NLP.
|
cs/9912011
|
Adaptivity in Agent-Based Routing for Data Networks
|
cs.MA adap-org cs.NI nlin.AO
|
Adaptivity, both of the individual agents and of the interaction structure
among the agents, seems indispensable for scaling up multi-agent systems
(MAS's) in noisy environments. One important consideration in designing
adaptive agents is choosing their action spaces to be as amenable as possible
to machine learning techniques, especially to reinforcement learning (RL)
techniques. One important way to have the interaction structure connecting
agents itself be adaptive is to have the intentions and/or actions of the
agents be in the input spaces of the other agents, much as in Stackelberg
games. We consider both kinds of adaptivity in the design of a MAS to control
network packet routing.
We demonstrate on the OPNET event-driven network simulator the perhaps
surprising fact that simply changing the action space of the agents to be
better suited to RL can result in very large improvements in their potential
performance: at their best settings, our learning-amenable router agents
achieve throughputs up to three and one half times better than that of the
standard Bellman-Ford routing algorithm, even when the Bellman-Ford protocol
traffic is maintained. We then demonstrate that much of that potential
improvement can be realized by having the agents learn their settings when the
agent interaction structure is itself adaptive.
|
cs/9912012
|
Avoiding Braess' Paradox through Collective Intelligence
|
cs.DC adap-org cs.MA cs.NI nlin.AO
|
In an Ideal Shortest Path Algorithm (ISPA), at each moment each router in a
network sends all of its traffic down the path that will incur the lowest cost
to that traffic. In the limit of an infinitesimally small amount of traffic for
a particular router, its routing that traffic via an ISPA is optimal, as far as
cost incurred by that traffic is concerned. We demonstrate though that in many
cases, due to the side-effects of one router's actions on another routers
performance, having routers use ISPA's is suboptimal as far as global aggregate
cost is concerned, even when only used to route infinitesimally small amounts
of traffic. As a particular example of this we present an instance of Braess'
paradox for ISPA's, in which adding new links to a network decreases overall
throughput. We also demonstrate that load-balancing, in which the routing
decisions are made to optimize the global cost incurred by all traffic
currently being routed, is suboptimal as far as global cost averaged across
time is concerned. This is also due to "side-effects", in this case of current
routing decision on future traffic.
The theory of COllective INtelligence (COIN) is concerned precisely with the
issue of avoiding such deleterious side-effects. We present key concepts from
that theory and use them to derive an idealized algorithm whose performance is
better than that of the ISPA, even in the infinitesimal limit. We present
experiments verifying this, and also showing that a machine-learning-based
version of this COIN algorithm in which costs are only imprecisely estimated (a
version potentially applicable in the real world) also outperforms the ISPA,
despite having access to less information than does the ISPA. In particular,
this COIN algorithm avoids Braess' paradox.
|
cs/9912015
|
Comparative Analysis of Five XML Query Languages
|
cs.DB
|
XML is becoming the most relevant new standard for data representation and
exchange on the WWW. Novel languages for extracting and restructuring the XML
content have been proposed, some in the tradition of database query languages
(i.e. SQL, OQL), others more closely inspired by XML. No standard for XML query
language has yet been decided, but the discussion is ongoing within the World
Wide Web Consortium and within many academic institutions and Internet-related
major companies. We present a comparison of five, representative query
languages for XML, highlighting their common features and differences.
|
cs/9912016
|
HMM Specialization with Selective Lexicalization
|
cs.CL cs.LG
|
We present a technique which complements Hidden Markov Models by
incorporating some lexicalized states representing syntactically uncommon
words. Our approach examines the distribution of transitions, selects the
uncommon words, and makes lexicalized states for the words. We performed a
part-of-speech tagging experiment on the Brown corpus to evaluate the resultant
language model and discovered that this technique improved the tagging accuracy
by 0.21% at the 95% level of confidence.
|
cs/9912017
|
Mixed-Level Knowledge Representation and Variable-Depth Inference in
Natural Language Processing
|
cs.CL
|
A system is described that uses a mixed-level knowledge representation based
on standard Horn Clause Logic to represent (part of) the meaning of natural
language documents. A variable-depth search strategy is outlined that
distinguishes between the different levels of abstraction in the knowledge
representation to locate specific passages in the documents. A detailed
description of the linguistic aspects of the system is given. Mixed-level
representations as well as variable-depth search strategies are applicable in
fields outside that of NLP.
|
cs/9912021
|
Seeing the Forest in the Tree: Applying VRML to Mathematical Problems in
Number Theory
|
cs.MS cs.CE
|
We show how VRML (Virtual Reality Modeling Language) can provide potentially
powerful insight into the 3x + 1 problem via the introduction of a unique
geometrical object, called the 'G-cell', akin to a fractal generator. We
present an example of a VRML world developed programmatically with the G-cell.
The role of VRML as a tool for furthering the understanding the 3x+1 problem is
potentially significant for several reasons: a) VRML permits the observer to
zoom into the geometric structure at all scales (up to limitations of the
computing platform). b) VRML enables rotation to alter comparative visual
perspective (similar to Tukey's data-spinning concept). c) VRML facilitates the
demonstration of interesting tree features between collaborators on the
internet who might otherwise have difficulty conveying their ideas
unambiguously. d) VRML promises to reveal any dimensional dependencies among
3x+1 sequences.
|
hep-lat/0003009
|
Data storage issues in lattice QCD calculations
|
hep-lat cs.DB
|
I describe some of the data management issues in lattice Quantum
Chromodynamics calculations. I focus on the experience of the UKQCD
collaboration. I describe an attempt to use a relational database to store part
of the data produced by a lattice QCD calculation.
|
hep-lat/0505005
|
Parallel Programming with Matrix Distributed Processing
|
hep-lat cs.CE physics.comp-ph
|
Matrix Distributed Processing (MDP) is a C++ library for fast development of
efficient parallel algorithms. It constitues the core of FermiQCD. MDP enables
programmers to focus on algorithms, while parallelization is dealt with
automatically and transparently. Here we present a brief overview of MDP and
examples of applications in Computer Science (Cellular Automata), Engineering
(PDE Solver) and Physics (Ising Model).
|
hep-lat/9808001
|
Genetic Algorithm for SU(N) gauge theory on a lattice
|
hep-lat cs.NE
|
An Algorithm is proposed for the simulation of pure SU(N) lattice gauge
theories based on Genetic Algorithms(GAs). Main difference between GAs and
Metropolis methods(MPs) is that GAs treat a population of points at once, while
MPs treat only one point in the searching space. This provides GAs with
information about the assortment as well as the fitness of the evolution
function and producting a better solution. We apply GAs to SU(2) pure gauge
theory on a 2 dimensional lattice and show the results are consistent with
those given by MP and Heatbath methods(HBs). Thermalization speed of GAs is
especially faster than the simple MPs.
|
hep-lat/9809068
|
Genetic Algorithm for SU(2) Gauge Theory on a 2-dimensional Lattice
|
hep-lat cs.NE
|
An algorithm is proposed for the simulation of pure SU(N) lattice gauge
theories based on Genetic Algorithms(GAs). We apply GAs to SU(2) pure gauge
theory on a 2 dimensional lattice and show the results, the action per
plaquette and Wilson loops, are consistent with those by Metropolis method(MP)s
and Heatbath method(HB)s. Thermalization speed of GAs is especially faster than
the simple MPs.
|
math-ph/0211067
|
Method of Additional Structures on the Objects of a Monoidal Kleisli
Category as a Background for Information Transformers Theory
|
math-ph cs.MA math.CT math.MP
|
Category theory provides a compact method of encoding mathematical structures
in a uniform way, thereby enabling the use of general theorems on, for example,
equivalence and universal constructions. In this article we develop the method
of additional structures on the objects of a monoidal Kleisli category. It is
proposed to consider any uniform class of information transformers (ITs) as a
family of morphisms of a category that satisfy certain set of axioms. This
makes it possible to study in a uniform way different types of ITs, e.g.,
statistical, multivalued, and fuzzy ITs. Proposed axioms define a category of
ITs as a monoidal category that contains a subcategory (of deterministic ITs)
with finite products. Besides, it is shown that many categories of ITs can be
constructed as Kleisli categories with additional structures.
|
math-ph/0512026
|
MIMO Channel Correlation in General Scattering Environments
|
math-ph cs.IT math.IT math.MP
|
This paper presents an analytical model for the fading channel correlation in
general scattering environments. In contrast to the existing correlation
models, our new approach treats the scattering environment as non-separable and
it is modeled using a bi-angular power distribution. The bi-angular power
distribution is parameterized by the mean departure and arrival angles, angular
spreads of the univariate angular power distributions at the transmitter and
receiver apertures, and a third parameter, the covariance between transmit and
receive angles which captures the statistical interdependency between angular
power distributions at the transmitter and receiver apertures. When this third
parameter is zero, this new model reduces to the well known "Kronecker" model.
Using the proposed model, we show that Kronecker model is a good approximation
to the actual channel when the scattering channel consists of a single
scattering cluster. In the presence of multiple remote scattering clusters we
show that Kronecker model over estimates the performance by artificially
increasing the number of multipaths in the channel.
|
math-ph/9903036
|
Numerically Invariant Signature Curves
|
math-ph cs.CV math.MP
|
Corrected versions of the numerically invariant expressions for the affine
and Euclidean signature of a planar curve proposed by E.Calabi et. al are
presented. The new formulas are valid for fine but otherwise arbitrary
partitions of the curve. We also give numerically invariant expressions for the
four differential invariants parametrizing the three dimensional version of the
Euclidean signature curve, namely the curvature, the torsion and their
derivatives with respect to arc length.
|
math/0005058
|
An information-spectrum approach to joint source-channel coding
|
math.PR cs.IT math.IT
|
Given a general source $\sV=\{V^n\}\noi$ with {\em countably infinite} source
alphabet and a general channel $\sW=\{W^n\}\noi$ with arbitrary {\em abstract}
channel input and output alphabets, we study the joint source-channel coding
problem from the information-spectrum point of view. First, we generalize
Feinstein's lemma (direct part) and Verd\'u-Han's lemma (converse part) so as
to be applicable to the general joint source-channel coding problem. Based on
these lemmas, we establish a sufficient condition as well as a necessary
condition for the source $\sV$ to be reliably transmissible over the channel
$\sW$ with asymptotically vanishing probability of error. It is shown that our
sufficient condition coincides with the sufficient condition derived by Vembu,
Verd\'u and Steinberg, whereas our necessary condition is much stronger than
the necessary condition derived by them. Actually, our necessary condition
coincide with our sufficient condition if we disregard some asymptotically
vanishing terms appearing in those conditions. Also, it is shown that {\em
Separation Theorem} in the generalized sense always holds. In addition, we
demonstrate a sufficient condition as well as a necessary condition for the
$\vep$-transmissibility ($0\le \vep <1$). Finally, the separation theorem of
the traditional standard form is shown to hold for the class of sources and
channels that satisfy the (semi-) strong converse property.
|
math/0005281
|
Connections between Linear Systems and Convolutional Codes
|
math.OC cs.IT math.IT
|
The article reviews different definitions for a convolutional code which can
be found in the literature. The algebraic differences between the definitions
are worked out in detail. It is shown that bi-infinite support systems are dual
to finite-support systems under Pontryagin duality. In this duality the dual of
a controllable system is observable and vice versa. Uncontrollability can occur
only if there are bi-infinite support trajectories in the behavior, so finite
and half-infinite-support systems must be controllable. Unobservability can
occur only if there are finite support trajectories in the behavior, so
bi-infinite and half-infinite-support systems must be observable. It is shown
that the different definitions for convolutional codes are equivalent if one
restricts attention to controllable and observable codes.
|
math/0006233
|
Algorithmic Statistics
|
math.ST cs.IT cs.LG math.IT math.PR physics.data-an stat.TH
|
While Kolmogorov complexity is the accepted absolute measure of information
content of an individual finite object, a similarly absolute notion is needed
for the relation between an individual data sample and an individual model
summarizing the information in the data, for example, a finite set (or
probability distribution) where the data sample typically came from. The
statistical theory based on such relations between individual objects can be
called algorithmic statistics, in contrast to classical statistical theory that
deals with relations between probabilistic ensembles. We develop the
algorithmic theory of statistic, sufficient statistic, and minimal sufficient
statistic. This theory is based on two-part codes consisting of the code for
the statistic (the model summarizing the regularity, the meaningful
information, in the data) and the model-to-data code. In contrast to the
situation in probabilistic statistical theory, the algorithmic relation of
(minimal) sufficiency is an absolute relation between the individual model and
the individual data sample. We distinguish implicit and explicit descriptions
of the models. We give characterizations of algorithmic (Kolmogorov) minimal
sufficient statistic for all data samples for both description modes--in the
explicit mode under some constraints. We also strengthen and elaborate earlier
results on the ``Kolmogorov structure function'' and ``absolutely
non-stochastic objects''--those rare objects for which the simplest models that
summarize their relevant information (minimal sufficient statistics) are at
least as complex as the objects themselves. We demonstrate a close relation
between the probabilistic notions and the algorithmic ones.
|
math/0009018
|
Critical Behavior in Lossy Source Coding
|
math.PR cs.IT math.IT
|
The following critical phenomenon was recently discovered. When a memoryless
source is compressed using a variable-length fixed-distortion code, the fastest
convergence rate of the (pointwise) compression ratio to the optimal $R(D)$
bits/symbol is either $O(\sqrt{n})$ or $O(\log n)$. We show it is always
$O(\sqrt{n})$, except for discrete, uniformly distributed sources.
|
math/0010173
|
Hot-pressing process modeling for medium density fiberboard (MDF)
|
math.NA cs.CE
|
In this paper we present a numerical solution for the mathematical modeling
of the hot-pressing process applied to medium density fiberboard. The model is
based in the work of Humphrey[82], Humphrey and Bolton[89] and Carvalho and
Costa[98], with some modifications and extensions in order to take into account
mainly the convective effects on the phase change term and also a conservative
numerical treatment of the resulting system of partial differential equations.
|
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