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
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;
Conference_Titel :
Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-8041-8
DOI :
10.1109/COGINF.2010.5599689