DocumentCode :
2563503
Title :
Clustering search engine query log containing noisy clickthroughs
Author :
Chan, Wing Shun ; Leung, Wai Ting ; Lee, Dik Lun
Author_Institution :
Dept. of Comput. Sci., Hong Kong Univ. of Sci. & Technol., Kowloon, China
fYear :
2004
fDate :
2004
Firstpage :
305
Lastpage :
308
Abstract :
Query clustering is a technique for discovering similar queries on a search engine. In this paper, we present a query clustering method based on the agglomerative clustering algorithm. We first present an overview of the agglomerative clustering algorithm proposed by Beeferman and Berger (2000). We point out a weakness of the method caused by noisy user clicks and propose an improved clustering algorithm. Our results show that in general the agglomerative clustering algorithm can cluster similar queries effectively and that our improved algorithm can successful eliminate noisy clicks and produce cleaner query clusters.
Keywords :
Internet; data mining; pattern clustering; query processing; search engines; Internet; agglomerative clustering algorithm; noisy clickthroughs; query clustering; query log clustering; search engines; similar query discovery; Bipartite graph; Clustering algorithms; Clustering methods; Computer science; Internet; Iterative algorithms; Search engines; Web pages;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applications and the Internet, 2004. Proceedings. 2004 International Symposium on
Print_ISBN :
0-7695-2068-5
Type :
conf
DOI :
10.1109/SAINT.2004.1266134
Filename :
1266134
Link To Document :
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