Combining passage-level and document-level evidence in information retrieval

Large collections of full-text documents are now commonly used in automated information retrieval. When the stored documents are long, the retrieval of complete documents may not be in the user's best interest. In this case, efficient and effective retrieval results may be obtained by retrievin...

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Main Author:	Xu, Richard Rong.
Other Authors:	School of Applied Science
Format:	Theses and Dissertations
Language:	English
Published:	2010
Subjects:	DRNTU::Library and information science::Libraries::Information retrieval and analysis
Online Access:	http://hdl.handle.net/10356/42542
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-42542
record_format	dspace
spelling	sg-ntu-dr.10356-425422020-09-27T20:15:00Z Combining passage-level and document-level evidence in information retrieval Xu, Richard Rong. School of Applied Science Chris Khoo DRNTU::Library and information science::Libraries::Information retrieval and analysis Large collections of full-text documents are now commonly used in automated information retrieval. When the stored documents are long, the retrieval of complete documents may not be in the user's best interest. In this case, efficient and effective retrieval results may be obtained by retrieving text excerpts of varying size in response to statements of the user's interest. This study explores a particular approach of segmenting text into passages for retrieval.Documents are segmented into passages by extracting a fixed number of contagious words from the whole document.The process of extracting passages can be viewed as using a window of certain size that slides through the whole document. Master of Science (Information Studies) 2010-12-30T03:55:35Z 2010-12-30T03:55:35Z 1999 1999 Thesis http://hdl.handle.net/10356/42542 en 143 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
topic	DRNTU::Library and information science::Libraries::Information retrieval and analysis
spellingShingle	DRNTU::Library and information science::Libraries::Information retrieval and analysis Xu, Richard Rong. Combining passage-level and document-level evidence in information retrieval
description	Large collections of full-text documents are now commonly used in automated information retrieval. When the stored documents are long, the retrieval of complete documents may not be in the user's best interest. In this case, efficient and effective retrieval results may be obtained by retrieving text excerpts of varying size in response to statements of the user's interest. This study explores a particular approach of segmenting text into passages for retrieval.Documents are segmented into passages by extracting a fixed number of contagious words from the whole document.The process of extracting passages can be viewed as using a window of certain size that slides through the whole document.
author2	School of Applied Science
author_facet	School of Applied Science Xu, Richard Rong.
format	Theses and Dissertations
author	Xu, Richard Rong.
author_sort	Xu, Richard Rong.
title	Combining passage-level and document-level evidence in information retrieval
title_short	Combining passage-level and document-level evidence in information retrieval
title_full	Combining passage-level and document-level evidence in information retrieval
title_fullStr	Combining passage-level and document-level evidence in information retrieval
title_full_unstemmed	Combining passage-level and document-level evidence in information retrieval
title_sort	combining passage-level and document-level evidence in information retrieval
publishDate	2010
url	http://hdl.handle.net/10356/42542
_version_	1681056859260190720

Combining passage-level and document-level evidence in information retrieval

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