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New Technology of Library and Information Service  2010, Vol. 26 Issue (5): 23-28    DOI: 10.11925/infotech.1003-3513.2010.05.05
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The Design and Implementation of the Bibliographic Recommendation System Based on Maximal Frequent Patterns Mining Algorithm
Zhao Lin
(Nankai University Library, Tianjin 300071, China)
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Abstract  

On the foundation of the Unicorn system in Nankai University Library, this paper introduces the design and implementation of bibliographic recommendation system based on  maximal frequent patterns mining algorithm. It describes the process of analyzing the readers’ behavior patterns by fully utilizing the accumulation data collected in the Unicorn system in details, so as to offer personalized bibliographic recommendation service. By using this system, the academic library can effectively expand different service patterns to readers on available sources, and improve the efficiency of the existing automated circulation system.

Key wordsPersonalized bibliographic recommendation        Data miningFrequent pattern tree (FP-Tree)         Maximal frequent patterns         FP-Growth     
Received: 01 March 2010      Published: 25 May 2010
: 

G250.7

 
Corresponding Authors: Zhao Lin     E-mail: kylin_zhao@yeah.net

Cite this article:

Zhao Lin. The Design and Implementation of the Bibliographic Recommendation System Based on Maximal Frequent Patterns Mining Algorithm. New Technology of Library and Information Service, 2010, 26(5): 23-28.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2010.05.05     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2010/V26/I5/23

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