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  5. An improved method for text summarization using lexical chains
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An improved method for text summarization using lexical chains

Date Issued
August 1, 2001
Author(s)
Byler, Charles Ray
Advisor(s)
Michael D. Vose
Additional Advisor(s)
Bethany K. Dumas
Bruce J. MacLennan
Bradley T. Vander Zanden
Permanent URI
https://trace.tennessee.edu/handle/20.500.14382/29711
Abstract

This work is directed toward the creation of a system for automatically sum-marizing documents by extracting selected sentences. Several heuristics including position, cue words, and title words are used in conjunction with lexical chain in-formation to create a salience function that is used to rank sentences for extraction. Compiler technology, including the Flex and Bison tools, is used to create the AutoExtract summarizer that extracts and combines this information from the raw text. The WordNet database is used for the creation of the lexical chains. The AutoExtract summarizer performed better than the Microsoft Word97 AutoSummarize tool and the Sinope commercial summarizer in tests against ideal extracts and in tests judged by humans.

Degree
Doctor of Philosophy
Major
Computer Science
File(s)
Thumbnail Image
Name

Thesis2001b.B895.pdf

Size

10.32 MB

Format

Unknown

Checksum (MD5)

04634586580e3179750c4bb751757715

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