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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/1252

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dc.contributor.authorSingh, Shailendra-
dc.contributor.authorDey, Lipika-
dc.date.accessioned2006-01-24T08:24:11Z-
dc.date.available2006-01-24T08:24:11Z-
dc.date.issued2003-
dc.identifier.citationInformation Processing & Management, 41(2), 195-216en
dc.identifier.urihttp://eprint.iitd.ac.in/dspace/handle/2074/1252-
dc.description.abstractDue to the large repository of documents available on the web, users are usually inundated by a large volume of information, most of which is found to be irrelevant. Since user perspectives vary, a client-side text filtering system that learns the user's perspective can reduce the problem of irrelevant retrieval. In this paper, we have provided the design of a customized text information filtering system which learns user preferences and modifies the initial query to fetch better documents. It uses a rough-fuzzy reasoning scheme. The rough-set based reasoning takes care of natural language nuances, like synonym handling, very elegantly. The fuzzy decider provides qualitative grading to the documents for the user's perusal. We have provided the detailed design of the various modules and some results related to the performance analysis of the system.en
dc.format.extent996154 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoenen
dc.subjectText information retrievalen
dc.subjectRough-set based reasoningen
dc.subjectFuzzy membershipen
dc.subjectDocument relevance computationen
dc.subjectUser preference learningen
dc.titleA rough-fuzzy document grading system for customized text information retrievalen
dc.typeArticleen
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