A Generalized Association Rule Mining Algorithm for Library New Book Recommendation

doi:10.11925/infotech.1003-3513.2006.10.04

New Technology of Library and Information Service

2006, Vol. 1

Issue (10): 16-20 DOI: 10.11925/infotech.1003-3513.2006.10.04

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A Generalized Association Rule Mining Algorithm for Library New Book Recommendation

She Junsheng Huang Zhan

(Department of Computer Science, Jinan University, Guangzhou 510632, China)

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Abstract

Based on MMS_Cumulate algorithm and GP-Apriori algorithm, a data mining algorithm, MAR_LCR is proposed for library new book recommendation service which is capable of finding generalized association rules in the form of “reader-book” and allows the user to specify multiple minimum supports for different items. The search space is greatly cut down by improving the process of candidate generation. Experiment results show that the MAR_LCR algorithm is highly effective. Finally, a new book recommendation model is proposed.

Key words： Generalized association rule Multiple minimum supports New book recommendation Library

Received: 22 June 2006 Published: 25 October 2006

TP311.13

Corresponding Authors: Huang Zhan E-mail: thz@jnu.edu.cn

About author:: She Junsheng,Huang Zhan

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Cite this article:

She Junsheng,Huang Zhan . A Generalized Association Rule Mining Algorithm for Library New Book Recommendation. New Technology of Library and Information Service, 2006, 1(10): 16-20.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2006.10.04 OR https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2006/V1/I10/16

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