Using lexical chains for text summarization

Regina Barzilay, Michael Elhadad

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

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, shallow parser for the identification of nominal groups, and a segmentation algorithm. Summarization proceeds in four steps: the original text is segmented, lexical chains are constructed strong chains are identified and significant sentences are extracted.
Original languageEnglish
Title of host publicationAdvances in automatic text summarization
EditorsInderjeet Mani, Mark T Maybury
PublisherThe MIT Press
Pages111-121
Number of pages11
StatePublished - 1999

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