Personalized information retrieval in digital ecosystems

Dengya Zhu, Heinz Dreher
2008 2008 2nd IEEE International Conference on Digital Ecosystems and Technologies  
Search results personalization is considered a promising approach to boost the quality of text retrieval. In this paper, a personalized information retrieval paradigm is proposed which not only implicitly creates user profile by learning users' search history, search preferences, and desktop information by kNN algorithm; but also intends to deal with the problem of search concepts drift through adjusting the weight of category which represents users' search preference. By comparing the cosine
more » ... milarities between vectors represent personal valued search concepts in user profiles, and vectors represent search concepts in the retrieved search results, the search results will be tailed to better match users' information needs.
doi:10.1109/dest.2008.4635207 fatcat:hxxva4g2jbhyjmgwdphomfyigi