Intelligent knowledge recommendation system based on web log and cache data

Authors:
Xun Wang;Biwei Li
Affiliations:
College of Computer&Information Engineering, Zhejiang Gongshang University, Hangzhou, China;College of Computer&Information Engineering, Zhejiang Gongshang University, Hangzhou, China
Venue:
ICWL'06 Proceedings of the 5th international conference on Advances in Web Based Learning
Year:
2006

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Abstract

Personalized recommendation service based on the web is the current research focus of intelligent information retrieval and distant education. In this paper, an intelligent recommendation system is proposed. The system depends on the mining results of Web log and cache data, comprehensively evaluates the influence of navigation times, browsing period, and page volume. Through effective classification of the interested pages from Web log and cache data, the interest model of different user groups is established. Meanwhile, a method for recommending the valuable knowledge is put forward, which combines the approach of content-based filtering and collaborative filtering. Experiments demonstrate that the proposed recommendation method is feasible and effective.