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
fDate :
Aug. 30 2010-Sept. 3 2010
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;
Conference_Titel :
Database and Expert Systems Applications (DEXA), 2010 Workshop on
Conference_Location :
Bilbao
Print_ISBN :
978-1-4244-8049-4
DOI :
10.1109/DEXA.2010.66