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New Technology of Library and Information Service  2012, Vol. 28 Issue (6): 1-8    DOI: 10.11925/infotech.1003-3513.2012.06.01
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Personalized Book Recommendation Algorithm Based on Multi-interest Analysis in Library
Ma Jian, Du Zeyu, Li Shuqing
College of Information Engineering, Nanjing University of Finance & Economics, Nanjing 210046, China
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Abstract  This paper firstly constructs the multi-interest feature library from readers’ interest lexicon and index with update algorithms combining gradual forgetting strategy and sliding window, then calculates the similarity measures of readers’ interest lexicon and index with books, and adds the two similarity with linear superposition to propose an operable and extensible hybrid recommendation algorithm. This algorithm synthetically uses the index types of books in Chinese Library Classification, and effectively solves the problem of data sparseness. Finally, the paper achieves a personalized recommendation system of the library books, and correlative experimental results are introduced in details.
Key wordsPersonalized recommendation      Gradual forgetting strategy      Interest feature      Hybrid recommendation     
Received: 27 April 2012      Published: 30 August 2012



Cite this article:

Ma Jian, Du Zeyu, Li Shuqing. Personalized Book Recommendation Algorithm Based on Multi-interest Analysis in Library. New Technology of Library and Information Service, 2012, 28(6): 1-8.

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