Reference Hub1
Improving Mobile Web Navigation Using N-Grams Prediction Models

Improving Mobile Web Navigation Using N-Grams Prediction Models

Yongjian Fu, Hironmoy Paul, Namita Shetty
Copyright: © 2007 |Volume: 3 |Issue: 2 |Pages: 14
ISSN: 1548-3657|EISSN: 1548-3665|ISSN: 1548-3657|EISBN13: 9781615203673|EISSN: 1548-3665|DOI: 10.4018/jiit.2007040104
Cite Article Cite Article

MLA

Fu, Yongjian, et al. "Improving Mobile Web Navigation Using N-Grams Prediction Models." IJIIT vol.3, no.2 2007: pp.51-64. http://doi.org/10.4018/jiit.2007040104

APA

Fu, Y., Paul, H., & Shetty, N. (2007). Improving Mobile Web Navigation Using N-Grams Prediction Models. International Journal of Intelligent Information Technologies (IJIIT), 3(2), 51-64. http://doi.org/10.4018/jiit.2007040104

Chicago

Fu, Yongjian, Hironmoy Paul, and Namita Shetty. "Improving Mobile Web Navigation Using N-Grams Prediction Models," International Journal of Intelligent Information Technologies (IJIIT) 3, no.2: 51-64. http://doi.org/10.4018/jiit.2007040104

Export Reference

Mendeley
Favorite Full-Issue Download

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.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.