Using Lexical Chains for Text Summarization

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Using Lexical Chains for Text Summarization (1997)

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by Resina Barzilay , Michael Elbadad

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451 - 8 self

BibTeX

@MISC{Barzilay97usinglexical,
    author = {Resina Barzilay and Michael Elbadad},
    title = {Using Lexical Chains for Text Summarization},
    year = {1997}
}

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Abstract

We investigate one technique to produce a summary of an original text without requiring its full semantic interpretation, but instead relying on a model of the topic progression in the text derived from lexical chains. We present a new algorithm to compute lexical chains in a text, merging several robust knowledge sources: the WordNet thesaurus, a part-of-speech tagger and shallow parser for the ldentification of nominal groups, and a segmentation algorithm derived from (Hearst, 1994) Summarization proceeds in three steps: the original text m first segmented, lexical chains are constructed, strong chains are identified and significant sentences are extracted from the text. We present in this paper empirical results on the identification of strong chain and of significant sentences.

Keyphrases

lexical chain text summarization significant sentence strong chain original text nominal group topic progression several robust knowledge source paper empirical result wordnet thesaurus new algorithm part-of-speech tagger summarization proceeds full semantic interpretation segmentation algorithm

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