DocumentCode
2539451
Title
Personalized search based on learning user click history
Author
Chen, Cheqian ; Lin, Kequan ; Li, Heshan ; Dong, Shoubin
Author_Institution
Sch. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou, China
fYear
2010
fDate
7-9 July 2010
Firstpage
490
Lastpage
495
Abstract
Nowadays, Web Search Engines have become an indispensable tool for people to find internet resources. However, current Web Search Engines still have many drawbacks. They serve all people in the same way, regardless of the individual needs of each user, which obviously cannot satisfy most of the users. Personalized Search is proposed to solve this problem and to improve the retrieve quality. This paper deeply investigates the approach for personalized search, and has proposed a practical and effective method.
Keywords
Internet; personal information systems; query processing; search engines; Internet resources; Web search engines; learning user click history; personalized search; query expansion; Algorithm design and analysis; Bayesian methods; Classification algorithms; Search engines; Sorting; Support vector machines; Training; Personalization; clickthrough data; search engine; user preferences;
fLanguage
English
Publisher
ieee
Conference_Titel
Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-8041-8
Type
conf
DOI
10.1109/COGINF.2010.5599689
Filename
5599689
Link To Document