J4 ›› 2011, Vol. 46 ›› Issue (5): 28-33.

• Articles • Previous Articles     Next Articles

A collaborative filtering recommendation mechanism based on user profile in unstructured P2P networks

LIU Jian1, YIN Chun-xia 2*, YUAN Fu-yong3   

  1. 1. Basic Department, Hebei Vocational College of Foreign Languages, Qinhuangdao 066311, Hebei,  China;
    2. College of Ocean, Hebei Agricultural University, Qinhuangdao 066003, Hebei, China;
    3. College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004, Hebei, China
  • Received:2010-12-06 Published:2011-05-25


Nowadays, collaborative filtering is one of the most successful technologies applyed in information recommender systems. However, with increase of the number of users and the amount of information needed to filter, the systems′ computational complexity quickly increases, and most centralized recommender systems have to face the low scalability problem. To solve the scalability problem of the recommender systems, a distributed collaborative filtering recommendation mechanism with an unstructured P2P architecture is proposed. In the recommendation mechanism, the content of resource is  represented by a vector according to the lexical chain method, and then the user profile can be represented by a preferred resource set. In addition, with the change of the user′s interest, the proposed mechanism also utilizes dynamic neighbor peer set reformation to gain a real time personalized recommendation.

Key words:  P2P; collaborative filtering; user profile; personalized recommendation

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