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New Technology of Library and Information Service  2012, Vol. 28 Issue (2): 18-22    DOI: 10.11925/infotech.1003-3513.2012.02.03
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Research on Users' Polymorphic Clustering in Personality Recommendation System
Liu Jiantao
Library of Huaqiao University, Quanzhou 362021, China
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Abstract  Traditional collaborative filtering algorithm is usually dependent on single kind of user requirement to generate clustering and this may affect the accuracy of recommendation. In view of the problem, this paper proposes a personalized recommendation method in digital library based on users' polymorphic clustering. This method uses an improved Hamming distance to calculate candidate neighbors, then combines polymorphic similarity to cluster again, finally forecasts user' s requirements degree and generates recommendation. The experiments show that recommendation based on polymorphic clustering is more accurate than the single' s.
Key wordsDigital library      Personalized recommendation      Polymorphism      Collaborative filtering     
Received: 26 December 2011      Published: 23 March 2012



Cite this article:

Liu Jiantao. Research on Users' Polymorphic Clustering in Personality Recommendation System. New Technology of Library and Information Service, 2012, 28(2): 18-22.

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