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Agricultural Library and Information ›› 2019, Vol. 31 ›› Issue (5): 50-60.doi: 10.13998/j.cnki.issn1002-1248.2019.05.19-0154

• Research paper • Previous Articles     Next Articles

Study on Personalized Book Recommendation Service for New College Readers

WANG Shengbin   

  1. Beihua University,Jilin Jilin 132013, China
  • Received:2019-03-05 Online:2019-05-05 Published:2019-05-05

Abstract: [Purpose/Significance]Aimed at the user cold start problem that prevent the university smart library from accurately recommending books to new readers, a personalized recommendation method for new college readers is proposed to provide practical solutions for carrying out personalized recommendation service and increasing new readers' borrowing rate.[Method/Process]Through data mining on borrowing circulating big data in Beihua university library, the conclusion is reached that new readers and existing readers with similar attributes have similar borrowing and reading preferences;Then, the singular value decomposition is used to solve the data sparse problem and the Euclidean distance and ant colony algorithm are used to cluster the new readers and existing readers, which building a bridge between new readers and existing readers. Finally, the Top-N algorithm is adopted to recommend the books borrowed by existing readers to new readers. [Result/Conclusion]Take the readers from grade 2017 as experiment subject, the proposed algorithm was tested on 44 readers from three academies. The results show that the proposed algorithm is effective and easy to operate, which lays a foundation for the subsequent personalized recommendation work.

Key words: new readers, personalized recommendation, user cold start, data sparsity, clustering

CLC Number: 

  • G252
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