Volume 8 Number 5 (May 2013)
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JCP 2013 Vol.8(5): 1351-1356 ISSN: 1796-203X
doi: 10.4304/jcp.8.5.1351-1356

Mining Web Logs with PLSA Based Prediction Model to Improve Web Caching Performance

Chuibi Huang1, Jinlin Wang2, Haojiang Deng2, and Jun Chen2
1 Department of Automation, USTC Key laboratory of network communication system and control Hefei, China
2 Institute of Acoustics, Chinese Academy of Sciences National Network New Media Engineering Research Center Beijing, China


Abstract—Web caching is a well-known strategy for improving the performance of web systems. The key to better web caching performance is an efficient replacing policy that keeps in the cache popular documents and replaces rarely used ones. When coupled with web log mining, the replacing policy can more accurately decide which documents should be cached. In this paper, we present a PLSA based prediction model to predict the user access patterns and interest to extend the well-known NGRAM-GDSF caching policy. Extensive experiments are conducted on the publicly available web logs datasets. The result shows that our approach gets better web-access performance

Index Terms—PLSA, web caching, web caching algorithm, prediction model, web log mining

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Cite: Chuibi Huang, Jinlin Wang, Haojiang Deng, and Jun Chen, " Mining Web Logs with PLSA Based Prediction Model to Improve Web Caching Performance," Journal of Computers vol. 8, no. 5, pp. 1351-1356, 2013.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Monthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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