Please use this identifier to cite or link to this item: http://hdl.handle.net/1813/7212
 Title: Automatic Text Decomposition Using Text Segments and Text Themes Authors: Salton, GerardSinghal, AmitBuckley, ChrisMitra, Mandar Keywords: computer sciencetechnical report Issue Date: Nov-1995 Publisher: Cornell University Citation: http://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR95-1555 Abstract: With the widespread use of full-text information retrieval, passage-retrieval techniques are becoming increasingly popular. Larger texts can then be replaced by important text excerpts, thereby simplifying the retrieval task and improving retrieval effectiveness. Passage-level evidence about the use of words in local contexts is also useful for resolving language ambiguities and improving retrieval output. Two main text decomposition strategies are introduced in this study, including a chronological decomposition into {\em text segments}, and semantic decomposition into {\em text themes}. The interaction between text segments and text themes is then used to characterize text structure, and to formulate specifications for information retrieval, text traversal, and text summarization. URI: http://hdl.handle.net/1813/7212 Appears in Collections: Computer Science Technical Reports

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