Combining sources of evidence for recognition of relevant passages in texts

Alexander Gelbukh, Namo Kang, Sangyong Han

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Automatically recognizing in large electronic texts short selfcontained passages relevant for a user query is necessary for fast and accurate information access to large text archives. Surprisingly, most search engines practically do not provide any help to the user in this tedious task, just presenting a list of whole documents supposedly containing the requested information. We show how different sources of evidence can be combined in order to assess the quality of different passages in a document and present the highest ranked ones to the user. Specifically, we take into account the relevance of a passage to the user query, structural integrity of the passage with respect to paragraphs and sections of the document, and topic integrity with respect to topic changes and topic threads in the text. Our experiments show that the results are promising.

Original languageEnglish
Title of host publicationAdvanced Distributed Systems - 5th International School and Symposium, ISSADS 2005, Revised Selected Papers
PublisherSpringer Verlag
Pages283-290
Number of pages8
ISBN (Print)3540280634, 9783540280637
DOIs
StatePublished - 2005
EventAdvanced Distributed Systems - 5th International School and Symposium, ISSADS 2005, Revised Selected Papers - Guadalajara, Mexico
Duration: 24 Jan 200528 Jan 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3563 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceAdvanced Distributed Systems - 5th International School and Symposium, ISSADS 2005, Revised Selected Papers
Country/TerritoryMexico
CityGuadalajara
Period24/01/0528/01/05

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