Title :
Selective Approach To Handling Topic Oriented Tasks On The World Wide Web
Author :
Awekar, Amit C. ; Kang, Jaewoo
Author_Institution :
North Carolina State Univ., Raleigh, NC
fDate :
March 1 2007-April 5 2007
Abstract :
We address the problem of handling topic oriented tasks on the World Wide Web. Our aim is to find most relevant and important pages for broad-topic queries while searching in a small set of candidate pages. We present a link analysis based algorithm SelHITS which is an improvement over Kleinberg´s HITS algorithm. We introduce concept of virtual links to exploit latent information in the hyperlinked environment. Selective expansion of the root set and novel ranking strategy are the distinguishing features of our approach. Selective expansion method avoids topic drift and provides results consistent with only one interpretation of the query. Experimental evaluation and user feedback show that our algorithm indeed distills the most relevant and important pages for broad-topic queries. Trends in user feedback suggests that there exists a uniform notion of quality of search results within users
Keywords :
Internet; information analysis; query formulation; relevance feedback; HITS algorithm; SelHITS algorithm; World Wide Web; broad-topic queries; hyperlinked environment; link analysis; ranking strategy; selective expansion method; topic oriented tasks; user feedback; virtual links; Computational intelligence; Computer languages; Data mining; Fires; Information retrieval; Java; Search engines; USA Councils; Web sites; World Wide Web;
Conference_Titel :
Computational Intelligence and Data Mining, 2007. CIDM 2007. IEEE Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
1-4244-0705-2
DOI :
10.1109/CIDM.2007.368894