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Improving the Compression Efficiency for News Web Service Using Semantic Relations Among Webpages

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  • Xiao Wei

    (Shanghai University, Shanghai, China & Shanghai Institute of Technology, Shanghai, China & City University of Hong Kong, Hong Kong)

  • Xiangfeng Luo

    (Shanghai University, Shanghai, China)

  • Qing Li

    (City University of Hong Kong, Hong Kong)

Abstract

Both compression and decompression play important roles in a web service system. High compression ratio helps to save the storage, while fast decompression contributes to decreasing the response time of service. Specifically focusing on the news web service, this paper proposes a compression mechanism to improve the efficiency of compression and decompression simultaneously by taking advantage of the semantic relations among webpages. Firstly, webpages are clustered into news topics according to the similarity semantic relation among webpages. Webpages belonging to the same topic have much duplicate content, which can improve the compression ratio when using delta-compression. Secondly, associated news topics are detected with the help of multiple-semantics link network of news topics. Associated topics are compressed into the same zip file which may decrease the times of decompression according to the habit of a user’s reading news on the Web. The authors apply the proposed compression mechanism to a practical news search engine and the experimental results show that it has high compression ratio and fast decompression speed as well.

Suggested Citation

  • Xiao Wei & Xiangfeng Luo & Qing Li, 2013. "Improving the Compression Efficiency for News Web Service Using Semantic Relations Among Webpages," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 7(2), pages 49-64, April.
    • Handle: RePEc:igg:jcini0:v:7:y:2013:i:2:p:49-64
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