One Improved Collaborative Filtering Method Based on Information Transformation | Zendy

Zhaoxing Liu | Zendy; Ning Zhang | Zendy

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One Improved Collaborative Filtering Method Based on Information Transformation

Author(s) -

Zhaoxing Liu,

Ning Zhang

Publication year - 2010

Publication title -

computer and information science

Language(s) - English

Resource type - Journals

eISSN - 1913-8997

pISSN - 1913-8989

DOI - 10.5539/cis.v4n1p186

Subject(s) - collaborative filtering , computer science , similarity (geometry) , hamming distance , bipartite graph , rank (graph theory) , transformation (genetics) , process (computing) , data mining , information retrieval , recommender system , degree (music) , algorithm , theoretical computer science , artificial intelligence , mathematics , graph , biochemistry , chemistry , physics , combinatorics , gene , acoustics , image (mathematics) , operating system

In this paper, we propose a novel method combined classical collaborative filtering (CF) and bipartite network structure. Different from the classical CF, user similarity is viewed as personal recommendation power and during the recommendation process; it will be redistributed to different users. Furthermore, a free parameter is introduced to tune the contribution of the user to the user similarity. Numerical results demonstrate that decreasing the degree of user to some extent in method performs well in rank value and hamming distance. Furthermore, the correlation between degree and similarity is concerned to solved the drastically change of our method performance.

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