Word Clustering and Disambiguation Based on Co-occurrence Data
We address the problem of clustering words (or constructing a thesaurus) based on co-occurrence data, and using the acquired word
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Word Length Frequency and Distribution in English: Observations, Theory, and Implications for the Construction of Verse Lines
Recent observations in the theory of verse and empirical metrics have suggested that constructing a verse line involves a pattern-matching
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Word Sense Disambiguation by Web Mining for Word Co-occurrence Probabilities
This paper describes the National Research Council (NRC) Word Sense Disambiguation (WSD) system, as applied to the English Lexical Sample
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Word Sense Disambiguation using Optimised Combinations of Knowledge Sources
Word sense disambiguation algorithms, with few exceptions, have made use of only one lexical knowledge source. We describe a system
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Word-to-Word Models of Translational Equivalence
Parallel texts (bitexts) have properties that distinguish them from other kinds of parallel data. First, most words translate to only
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"I don't believe in word senses"
Word sense disambiguation assumes word senses. Within the lexicography and linguistics literature, they are known to be very slippery entities.
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A Classification Approach to Word Prediction
The eventual goal of a language model is to accurately predict the value of a missing word given its context.
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A Comparison between Supervised Learning Algorithms for Word Sense Disambiguation
This paper describes a set of comparative experiments, including cross-corpus evaluation, between five alternative algorithms for supervised Word Sense Disambiguation
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A Decision Tree of Bigrams is an Accurate Predictor of Word Sense
This paper presents a corpus-based approach to word sense disambiguation where a decision tree assigns a sense to an ambiguous
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A Microsoft Word Font for Anti-Matter
One often wishes to quickly add a few overlined characters such as anti-B0 or anti-neutrino to a Microsoft Word document.
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An Efficient, Probabilistically Sound Algorithm for Segmentation and Word Discovery
This paper presents a model-based, unsupervised algorithm for recovering word boundaries in a natural-language text from which they have been
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A Simple Approach to Building Ensembles of Naive Bayesian Classifiers for Word Sense Disambiguation
This paper presents a corpus-based approach to word sense disambiguation that builds an ensemble of Naive Bayesian classifiers, each of
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A statistical model for word discovery in child directed speech
A statistical model for segmentation and word discovery in child directed speech is presented. An incremental unsupervised learning algorithm to
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A Statistical Model for Word Discovery in Transcribed Speech
A statistical model for segmentation and word discovery in continuous speech is presented. An incremental unsupervised learning algorithm to infer
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Boosting Applied to Word Sense Disambiguation
In this paper Schapire and Singer's AdaBoost.MH boosting algorithm is applied to the Word Sense Disambiguation (WSD) problem. Initial experiments
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Choosing the Word Most Typical in Context Using a Lexical Co-occurrence Network
This paper presents a partial solution to a component of the problem of lexical choice: choosing the synonym most typical,
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Context Related Derivation of Word Senses
Real applications of natural language document processing are very often confronted with domain specific lexical gaps during the analysis of
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Corpus-Based Word Sense Disambiguation
Resolution of lexical ambiguity, commonly termed ``word sense disambiguation'', is expected to improve the analytical accuracy for tasks which are
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Deriving the Predicate-Argument Structure for a Free Word Order Language
In relatively free word order languages, grammatical functions are intricately related to case marking. Assuming an ordered representation of the
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Do not forget: Full memory in memory-based learning of word pronunciation
Memory-based learning, keeping full memory of learning material, appears a viable approach to learning NLP tasks, and is often superior
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Efficient dot product over word-size finite fields
We want to achieve efficiency for the exact computation of the dot product of two vectors over word-size finite fields.
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Entropy, Transinformation and Word Distribution of Information-Carrying Sequences
We investigate correlations in information carriers, e.g. texts and pieces of music, which are represented by strings of letters. For
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Exploring automatic word sense disambiguation with decision lists and the Web
The most effective paradigm for word sense disambiguation, supervised learning, seems to be stuck because of the knowledge acquisition bottleneck.
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Fine-Grained Word Sense Disambiguation Based on Parallel Corpora, Word Alignment, Word Clustering and Aligned Wordnets
The paper presents a method for word sense disambiguation based on parallel corpora. The method exploits recent advances in word
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