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Book Recommendation System Based on Folksonomy in Library |
Luo Lin, Liang Guisheng, Cai Jun |
Center for the Studies of Information Resources, Wuhan University, Wuhan 430072, China |
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Abstract [Objective] This paper tries to build a book recommender system based on folksonomy, which forms the triple relations among the users, resources and tags. [Methods] This papercalculates the cosine similarity and weights of books and tags, use sparse vector representation to represent the input matrix for each resource to compress sparse matrix. [Results] Experimental results show that the book weights varied from 0 to 200 and the tag weights followed a power law distribution. In the end, the relevant assessments are performed with the AP and MAP indicators. [Limitations] It fails to get enough data in the library catalogs, hence collects the additional data in book.douban.com. [Conclusions] The recommendation system can help the OPACs to improve its function and personalized services.
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Received: 30 December 2013
Published: 19 May 2014
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