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| Research on Ontology-based Personalized Recommendation Method for Library Resources |
| Wang Yingzi |
| Changzhou University Library, Changzhou 213164, China |
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Abstract The huge increase of library resources makes users’ cost of accessing valuable knowledge becoming much higher. For this problem, the paper proposes a hybrid recommendation method for library resources, which adopts semantic technologies to describe library resources and borrowers, establishes the association between user preferences and library resource features. Through query modification, rule-based and case-based inference, the method realizes personalized recommendation. Meanwhile, some auxiliary recommendation approaches are integrated. The recommendation process can be analyzed and optimized according to users’ feedback. Additionally, this method reduces the “new user” and “new item” problems in traditional collaborative filtering method to a certain extent. Experimental results show that the proposed method can enhance the hit rate.
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Received: 12 October 2012
Published: 12 March 2013
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