DocumentCode
2406546
Title
Web Page Classification Using Distributed Learning Automata and Partitioning Graph Algorithm
Author
Bazarganigilani, Mahdi ; Syed, Ali
Author_Institution
Fac. of Bus., Charles Sturt Univ., Melbourne, VIC, Australia
fYear
2010
fDate
Aug. 30 2010-Sept. 3 2010
Firstpage
302
Lastpage
304
Abstract
The characteristic of dynamic websites is that they include hidden contents, and this huge repository is only accessible via the website interfaces. This is a vital capability of all search engines, thus providing the users with links that are more relevant and ranked according to their needs. The drawback of most search engine algorithms is that they rank pages based on hyperlinked relative importance to other pages, rather than user intent and interest. This paper proposes a method based on Learning Automata for the classification of the webpage searches.
Keywords
Internet; graph theory; learning automata; pattern classification; search engines; user interfaces; Web page classification; Website interfaces; distributed learning automata; dynamic Websites characteristic; hidden contents; partitioning graph algorithm; rank pages; search engines; Classification algorithms; Clustering algorithms; Heuristic algorithms; Learning automata; Partitioning algorithms; Software algorithms; Web pages; Distributed Learning Automata; Graph Partitioning Algorithm; Web classification; component; web page ranking;
fLanguage
English
Publisher
ieee
Conference_Titel
Database and Expert Systems Applications (DEXA), 2010 Workshop on
Conference_Location
Bilbao
ISSN
1529-4188
Print_ISBN
978-1-4244-8049-4
Type
conf
DOI
10.1109/DEXA.2010.66
Filename
5591189
Link To Document