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