Title :
Web Pages Clustering and Concepts Mining: An approach towards Intelligent Information Retrieval
Author :
Li, Fang ; Mehlitz, Martin ; Feng, Li ; Sheng, Huanye
Author_Institution :
Dept. of Comput. Sci. & Eng., Shanghai Jiaotong Univ.
Abstract :
The amount of information on the Web is growing at an exponential rate. Information overload has brought a heavy burden for modern life. Keyword based search engines no long fill the needs of many people. This paper introduces an approach towards intelligent information retrieval by providing clustered Web pages and minded concepts based on results of search engines. Web page clustering is based on SVD (singular value decomposition), concepts mining is implemented with a revision of Apriori algorithm. Experiments on three different kinds of keyword as queries to information retrieval have showed a promising result
Keywords :
Internet; data mining; information retrieval; pattern clustering; search engines; singular value decomposition; Apriori algorithm; Web page clustering; World Wide Web; concept mining; information overload; intelligent information retrieval; keyword based search engine; singular value decomposition; Cities and towns; Clustering algorithms; Computer science; Image retrieval; Information retrieval; Internet; Metasearch; Search engines; Singular value decomposition; Web pages; clustering; concept mining; information retrieval;
Conference_Titel :
Cybernetics and Intelligent Systems, 2006 IEEE Conference on
Conference_Location :
Bangkok
Print_ISBN :
1-4244-0023-6
DOI :
10.1109/ICCIS.2006.252315
