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dc.contributor.authorOu, Shiyan
dc.contributor.authorKhoo, Christopher S.G.
dc.contributor.authorGoh, Dion H.
dc.date.accessioned2008-05-23T16:31:20Z
dc.date.available2008-05-23T16:31:20Z
dc.date.issued2008
dc.identifier.citationJournal of Information Science, 34 (3): 308-326
dc.identifier.issn01655515
dc.identifier.issn00000000
dc.identifier.doi10.1177/0165551507084630
dc.identifier.urihttp://hdl.handle.net/2436/27899
dc.description.abstractThis paper describes a new concept-based multi-document summarization system that employs discourse parsing, information extraction and information integration. Dissertation abstracts in the field of sociology were selected as sample documents for this study. The summarization process includes four major steps — (1) parsing dissertation abstracts into five standard sections; (2) extracting research concepts (often operationalized as research variables) and their relationships, the research methods used and the contextual relations from specific sections of the text; (3) integrating similar concepts and relationships across different abstracts; and (4) combining and organizing the different kinds of information using a variable-based framework, and presenting them in an interactive web-based interface. The accuracy of each summarization step was evaluated by comparing the system-generated output against human coding. The user evaluation carried out in the study indicated that the majority of subjects (70%) preferred the concept-based summaries generated using the system to the sentence-based summaries generated using traditional sentence extraction techniques.
dc.language.isoen
dc.publisherSage
dc.relation.urlhttp://jis.sagepub.com/cgi/content/abstract/34/3/308
dc.subjectDiscourse parsing
dc.subjectInformation extraction
dc.subjectInformation integration
dc.subjectMulti-document summarization
dc.titleDesign and development of a concept-based multi-document summarization system for research abstracts
dc.typeJournal article
dc.identifier.journalJournal of Information Science
html.description.abstractThis paper describes a new concept-based multi-document summarization system that employs discourse parsing, information extraction and information integration. Dissertation abstracts in the field of sociology were selected as sample documents for this study. The summarization process includes four major steps — (1) parsing dissertation abstracts into five standard sections; (2) extracting research concepts (often operationalized as research variables) and their relationships, the research methods used and the contextual relations from specific sections of the text; (3) integrating similar concepts and relationships across different abstracts; and (4) combining and organizing the different kinds of information using a variable-based framework, and presenting them in an interactive web-based interface. The accuracy of each summarization step was evaluated by comparing the system-generated output against human coding. The user evaluation carried out in the study indicated that the majority of subjects (70%) preferred the concept-based summaries generated using the system to the sentence-based summaries generated using traditional sentence extraction techniques.


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