DocumentCode
2639963
Title
Affinity-based probabilistic reasoning and document clustering on the WWW
Author
Shyu, Mei-Ling ; Chen, Shu-Ching ; Shu, Chi-Min
Author_Institution
Dept. of Electr. & Comput. Eng., Miami Univ., Coral Gables, FL, USA
fYear
2000
fDate
2000
Firstpage
149
Lastpage
154
Abstract
The World Wide Web (WWW) has become one of the fastest growing applications on the Internet today. More and more information sources have linked online through WWW, but finding information on the WWW is also a great challenge. For most users, the information retrieved is not well organized and the access time is considered high on the WWW currently. Therefore, there is a need to develop a good mechanism to organize and manage the tremendous size and various kinds of information to facilitate the functionality of a search engine for information retrieval on the WWW. In response to such a demand we propose a Markov Model Mediator (MMM) mechanism which employs affinity based data mining techniques to organize and manage the information sources so that the most relevant documents are clustered together to achieve higher recall and precision values for information retrieval on the WWW
Keywords
Markov processes; data mining; document handling; inference mechanisms; information resources; information retrieval; search engines; Internet; MMM mechanism; Markov Model Mediator; WWW; World Wide Web; access time; affinity based data mining techniques; affinity based probabilistic reasoning; document clustering; information retrieval; information sources; most relevant documents; precision values; search engine; Association rules; Computer science; Data mining; Electrical safety; Information retrieval; Internet; Search engines; Web server; Web sites; World Wide Web;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Software and Applications Conference, 2000. COMPSAC 2000. The 24th Annual International
Conference_Location
Taipei
ISSN
0730-3157
Print_ISBN
0-7695-0792-1
Type
conf
DOI
10.1109/CMPSAC.2000.884705
Filename
884705
Link To Document