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Generating Personalized Web Search Using Semantic Context
Joint Authors
Source
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-04-27
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
The “one size fits the all” criticism of search engines is that when queries are submitted, the same results are returned to different users.
In order to solve this problem, personalized search is proposed, since it can provide different search results based upon the preferences of users.
However, existing methods concentrate more on the long-term and independent user profile, and thus reduce the effectiveness of personalized search.
In this paper, the method captures the user context to provide accurate preferences of users for effectively personalized search.
First, the short-term query context is generated to identify related concepts of the query.
Second, the user context is generated based on the click through data of users.
Finally, a forgetting factor is introduced to merge the independent user context in a user session, which maintains the evolution of user preferences.
Experimental results fully confirm that our approach can successfully represent user context according to individual user information needs.
American Psychological Association (APA)
Xu, Zheng& Chen, Hai-Yan& Yu, Jie. 2015. Generating Personalized Web Search Using Semantic Context. The Scientific World Journal،Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1078780
Modern Language Association (MLA)
Xu, Zheng…[et al.]. Generating Personalized Web Search Using Semantic Context. The Scientific World Journal No. 2015 (2015), pp.1-10.
https://search.emarefa.net/detail/BIM-1078780
American Medical Association (AMA)
Xu, Zheng& Chen, Hai-Yan& Yu, Jie. Generating Personalized Web Search Using Semantic Context. The Scientific World Journal. 2015. Vol. 2015, no. 2015, pp.1-10.
https://search.emarefa.net/detail/BIM-1078780
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1078780