EPrints@IIT Delhi >
Faculty Research Publicatons  >
Mathematics >

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

Full metadata record

DC FieldValueLanguage
dc.contributor.authorSingh, Shailendra-
dc.contributor.authorDey, Lipika-
dc.identifier.citationInformation Processing & Management, 41(2), 195-216en
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.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
Appears in Collections:Mathematics

Files in This Item:

File Description SizeFormat
singhrou2003.pdf972.81 kBAdobe PDFView/Open
View Statistics

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.


Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback