A new integrated personalized recommendation algorithm

Authors:
Hongfang Zhou;Boqin Feng;Lintao Lv;Zhurong Wang
Affiliations:
School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, China;School of Electronics and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, China;School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, Shaanxi, China;School of Computer Science and Engineering, Xi’an University of Technology, Xi’an, Shaanxi, China
Venue:
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Year:
2005

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Abstract

Traditional information retrieval technologies can satisfy users’ needs to some extent. But they cannot satisfy any query from different backgrounds, with different intentions and at different time because of their all-purpose characteristics. An integrated searching algorithm by combining filtering with collaborative technologies is presented in this paper. The user model is represented as the probability distribution over the domain classification model. A method of computing similarity and a method of revising user model are provided. Compared with the vector space model, the probability model is more effective on describing users’ interests. Furthermore, collaborative-based technologies are used, and as a result the scalability of the new algorithm is highly enhanced.