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Personalized Web search for improving retrieval effectiveness

TitlePersonalized Web search for improving retrieval effectiveness
Publication TypeJournal Article
Year of Publication2004
AuthorsLiu, F, Yu, C, Meng, W
JournalKnowledge and Data Engineering, IEEE Transactions on
Volume16
Pagination28-40
Date PublishedJan
ISSN1041-4347
KeywordsBANDWIDTH, category hierarchy, category mapping algorithms, Displays, fusion algorithm, History, human factors, information filtering, information retrieval, libraries, personalized Web search, profile learning, retrieval effectiveness, search engines, search intention, special needs, user interfaces, user profiles, user search histories, Web search, Web search engines
Abstract

Current Web search engines are built to serve all users, independent of the special needs of any individual user. Personalization of Web search is to carry out retrieval for each user incorporating his/her interests. We propose a novel technique to learn user profiles from users' search histories. The user profiles are then used to improve retrieval effectiveness in Web search. A user profile and a general profile are learned from the user's search history and a category hierarchy, respectively. These two profiles are combined to map a user query into a set of categories which represent the user's search intention and serve as a context to disambiguate the words in the user's query. Web search is conducted based on both the user query and the set of categories. Several profile learning and category mapping algorithms and a fusion algorithm are provided and evaluated. Experimental results indicate that our technique to personalize Web search is both effective and efficient.

DOI10.1109/TKDE.2004.1264820
AttachmentSize
PDF icon PersonalizedWebSearch2004Liu.pdf1.11 MB