Generating Lexical Analogies Using Dependency Relations

نویسندگان

  • Andy Chiu
  • Pascal Poupart
  • Chrysanne Di Marco
چکیده

A lexical analogy is a pair of word-pairs that share a similar semantic relation. Lexical analogies occur frequently in text and are useful in various natural language processing tasks. In this study, we present a system that generates lexical analogies automatically from text data. Our system discovers semantically related pairs of words by using dependency relations, and applies novel machine learning algorithms to match these word-pairs to form lexical analogies. Empirical evaluation shows that our system generates valid lexical analogies with a precision of 70%, and produces quality output although not at the level of the best humangenerated lexical analogies.

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تاریخ انتشار 2007