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Enhancing Mobile Web Access Using Intelligent Recommendations
January/February 2006 (vol. 21 no. 1)
pp. 28-34
Baoyao Zhou, Nanyang Technological University
Siu Cheung Hui, Nanyang Technological University
Kuiyu Chang, Nanyang Technological University
As mobile phones continue to infiltrate the world, they could easily become the Internet client of choice—especially considering widespread adoption of third-generation mobile services. Although the mobile phone?s disproportionately small screen is ill-suited for Web surfing, it's here to stay because it's constrained by portability requirements. Using recommendations can aid mobile Web surfing. Unlike most Web recommendation approaches that use clustering and association rule mining, this approach identifies frequent sequential Web-access patterns. A tree structure called pattern-tree stores the patterns and then generates recommended links. Experimental evaluations of the approach illustrate its effectiveness.

This article is part of a special issue on AI, Agents, and the Web.

Index Terms:
mobile browsers, cell phones, Web usage mining, sequential Web-access patterns, Web recommendation, trie
Citation:
Baoyao Zhou, Siu Cheung Hui, Kuiyu Chang, "Enhancing Mobile Web Access Using Intelligent Recommendations," IEEE Intelligent Systems, vol. 21, no. 1, pp. 28-34, Jan.-Feb. 2006, doi:10.1109/MIS.2006.5
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