An Approach to Web Prefetching Agent Based on Web Ontology with Hidden Markov Model

Abstract

With the rapid growth of web services on the Internet, users are experiencing access delays more often than ever. Recent studies showed that web prefetching could alleviate the WWW latency to a larger extent than the traditional caching. Web prefetching is one of the most popular strategies in web mining research domain, which are proposed for reducing the perceived access delay, improving the service quality of web site and mining the user requirement information in advance. In this paper, we introduce the features of the web site model named web ontology, and build a web prefetching agent-WebAGENT based on the web ontology and the hidden Markov model. With the agent, we analyze the user access path and how to mine the latent information requirement concepts, then we could make semantic-based prefetching decisions. Experimental results show that the web prefetching scheme of the WebAGENT has better predictive mining effect and prefetching precision.

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References

  1. 1.
    Markatos, E.P., Chironaki, C.E.: A Top 10 Approach for prefetching the web. In: Proceedings of INET’98: Internet Global Summint (July 1998)Google Scholar
  2. 2.
    Schechter, S., Krishnan, M., Smith, M.D.: Using Path profiles to predict http requests. In: Proceedings of WWW7 (1998)Google Scholar
  3. 3.
    Yoon, S., Jin, E., Seo, J.: Multimedia Technology ResearchLab, Korea, Telcom, http://www.isoc.org/inet99/proceedings/posters/106
  4. 4.
    Deshpande, M., Karypis, G.: Selective Markov Models for Predicting Web_Page Accesses. In: Proceedings SIAM Int.Conference on Data Mining(SDM’2001) (Apr. 2001)Google Scholar
  5. 5.
    Sarukkai, R.R.: Link Prediction and Path analysis Using Markov Chains. In: 9th World Wide Web Conference (May 2001)Google Scholar
  6. 6.
    Xu, B.-w., Zhang, W.-f.: Applying Data Mining to Web Prefetching. Chinese J. Computers 24(4), 1–7 (2001)Google Scholar
  7. 7.
    Rabiner, L., Juang, R.-H.: Fundamentals of speech recognition, pp. 312–389. Prentice Hall, Englewood Cliffs (1993)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Xin Jin
    • 1
  1. 1.School of Information, Central University of Finance & Economics, Beijing, 100081P.R. China

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