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Using Information Content to Evaluate Semantic Similarity in a Taxonomy
TLDR
This paper presents a new measure of semantic similarity in an IS-A taxonomy, based on the notion of information content. Expand
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Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language
  • P. Resnik
  • Computer Science, Mathematics
  • J. Artif. Intell. Res.
  • 1 July 1999
TLDR
This article presents a measure of semantic similarity in an IS-A taxonomy based on the notion of shared information content that can be used to resolve syntactic and semantic ambiguity. Expand
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The Web as a Parallel Corpus
TLDR
We report on our work using the STRAND system for mining parallel text on the World Wide Web, first reviewing the original algorithm and results and presenting a set of significant enhancements. Expand
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Bootstrapping parsers via syntactic projection across parallel texts
TLDR
We explore using parallel text to help solving the problem of creating syntactic annotation in more languages. Expand
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Online Large-Margin Training of Syntactic and Structural Translation Features
TLDR
We show that by parallel processing and exploiting more of the parse forest, we can obtain results using MIRA that match or surpass MERT in terms of both translation quality and computational cost. Expand
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Selection and information: a class-based approach to lexical relationships
Selectional constraints are limitations on the applicability of predicates to arguments. For example, the statement "The number two is blue" may be syntactically well formed, but at some level it isExpand
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A Rule-Based Approach to Prepositional Phrase Attachment Disambiguation
TLDR
In this paper, we describe a new corpus-based approach to prepositional phrase attachment disambiguation. Expand
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Generalizing Word Lattice Translation
TLDR
Word lattice decoding has proven useful in spoken language translation; we argue that it provides a compelling model for translation of text genres, as well. Expand
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Disambiguating Noun Groupings with Respect to Wordnet Senses
  • P. Resnik
  • Computer Science
  • VLC@ACL
  • 29 November 1995
TLDR
We present a method for automatic sense disambiguation of nouns appearing within sets of related nouns — the kind of data one finds in thesauri, or as the output of distributional clustering algorithms. Expand
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Selectional Preference and Sense Disambiguation
  • P. Resnik
  • Computer Science
  • Workshop On Tagging Text With Lexical Semantics…
  • 1997
TLDR
This paper explores how a statistical model of selectional preference, requiring neither manual annotation of selection restrictions nor supervised training, can be used in sense disambiguation. Expand
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