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Improving Mobile Web Navigation Using N-Grams Prediction Models

Author

Listed:
  • Yongjian Fu

    (Cleveland State University, USA)

  • Hironmoy Paul

    (Cleveland State University, USA)

  • Namita Shetty

    (Cleveland State University, USA)

Abstract

In this article, we propose to use N-gram models for improving Web navigation for mo-bile users. N-gram models are built from Web server logs to learn navigation patterns of mobile users. They are used as prediction models in an existing algorithm which improves mobile Web navigation by recommending shortcuts. Our experiments on two real data sets show that N-gram models are as effective as other more complex models in improving mobile Web navigation.

Suggested Citation

  • Yongjian Fu & Hironmoy Paul & Namita Shetty, 2007. "Improving Mobile Web Navigation Using N-Grams Prediction Models," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 3(2), pages 51-64, April.
    • Handle: RePEc:igg:jiit00:v:3:y:2007:i:2:p:51-64
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