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New Technology of Library and Information Service  2008, Vol. 24 Issue (8): 42-47    DOI: 10.11925/infotech.1003-3513.2008.08.07
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A Personalized Web Pages Recommendation Model Based on Sequential Patterns
Yi Ming
(Department of Information Management， Huazhong Normal University， Wuhan  430079,China)
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Abstract  

This paper proposes a personalized Web pages recommendation model based on sequential patterns. Firstly, this model extracts the Web transaction set by Web usage preparation. Secondly, it applies a sequential patterns algorithm to discover frequent (contiguous) sequences. Finally, the model utilizes frequent (contiguous) sequences tree to generate user interest view and provides personalized recommendation set.
Key words： Sequential patterns      Personalized recommendation      Interest view     
Received: 24 September 2007      Published: 25 August 2008
: 

TP393

 		 
Corresponding Authors: Yi Ming     E-mail: yiming0415@sina.com
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Cite this article:

Yi Ming. A Personalized Web Pages Recommendation Model Based on Sequential Patterns. New Technology of Library and Information Service, 2008, 24(8): 42-47.

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https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2008.08.07     OR     https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2008/V24/I8/42

［1］ 谢中.基于Web数据挖掘商务网站推荐系统的研究［D］.重庆:西南师范大学,2002.
［2］ 童恒庆,梅清.Web日志挖掘数据预处理研究［J］.现代计算机,2004(3):6-9.
［3］ Colley R. Web Usage Mining:Discovery and Application of Interesting Patterns from Web Data［D］. Minneapolis:University of Minnesota, 2000.
［4］ Berendt B, Spiliopoulou M. Analysis of Navigation Behavior in Web Sites Integrating Multiple Information Systems［J］. The VLDB Journal, 2000(9):56-75.
［5］ Tan P N,  Kumar V. Discovery of Web Robot Sessions Based on their Navigational Patterns［J］. Data Mining and Knowledge Discovery, 2002 (1):9-35.
［6］ Berendt B, Mobasher B,  Spiliopoulou M, et al.Measuring the accuracy of sessionizers for web usage analysis［C］. In:Proceeding of  the First SIAM International Conference on Data Mining. Chicago, 2001:7-14.
［7］ Catledge L, Pitkow J. Characterizing Browsing Behaviors on the World Wide Web［J］. Computer Networks and ISDN Systems, 1995(6):1065-1073.
［8］ Cooley R,  Mobasher B,  Srivastava J. Data preparation for mining World Wide Web browsing patterns［J］. Journal of Knowledge and Information Systems, 1999(1):5-32.
［9］ 邵峰晶,于忠清.数据挖掘——原理与算法［M］.北京:中国水利水电出版社,2003:277-288.
［10］ Mobasher B. Web Usage Mining and Personalization. In:The Practical Handbook of Internet Computing［M］. Munindar P. Singh (ed.), Boca Raton:CRC Press, 2005:16-28.
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