Improving Mobile Web Navigation Using N-Grams Prediction Models

Improving Mobile Web Navigation Using N-Grams Prediction Models

Yongjian Fu (Cleveland State University, USA)
DOI: 10.4018/978-1-60566-144-5.ch017
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Abstract

In this chapter, we propose to use N-gram models for improving Web navigation for mobile users. Ngram 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.
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We briefly discuss Web usage mining techniques and its applications in adaptive Web sites and mobile Web navigation.

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