DocumentCode
658645
Title
Tolerance Rough Set Model and Its Applications in Web Intelligence
Author
Hung Son Nguyen
Author_Institution
Inst. of Math., Univ. of Warsaw, Warsaw, Poland
Volume
3
fYear
2013
fDate
17-20 Nov. 2013
Firstpage
237
Lastpage
244
Abstract
Tolerance Rough Set Model (TRSM) has been introduced as a tool for approximation of hidden concepts in text databases. In recent years, numerous successful applications of TRSM in web intelligence including text classification, clustering, thesaurus generation, semantic indexing, and semantic search, etc., have been proposed. This paper will review the fundamental concepts of TRSM, some of its possible extensions and some typical applications of TRSM in text mining. Moreover, the architecture o a semantic information retrieval system, called SONCA, will be presented to demonstrate the main idea as well as stimulate the further research on TRSM.
Keywords
data mining; information retrieval systems; ontologies (artificial intelligence); rough set theory; text analysis; SONCA system; TRSM; Web intelligence; clustering; search based on ontologies and compound analytics; semantic indexing; semantic information retrieval system; semantic search; text classification; text databases; text mining; thesaurus generation; tolerance rough set model; Approximation methods; Indexes; Information retrieval; Ontologies; Semantics; Standards; Vectors; Tolerance rough set model; classification; clustering; semantic indexing; semantic search;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2013 IEEE/WIC/ACM International Joint Conferences on
Conference_Location
Atlanta, GA
Print_ISBN
978-1-4799-2902-3
Type
conf
DOI
10.1109/WI-IAT.2013.189
Filename
6690734
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