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Adaptive Web Browsing Using Web Mining Technologies for Internet Enabled Mobile Handheld Devices

Adaptive Web Browsing Using Web Mining Technologies for Internet Enabled Mobile Handheld Devices
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Author(s): Wen-Chen Hu (University of North Dakota, USA), Jyh-haw Yeh (Boise State University, USA), Hung-Ju Chu (University of Florida, USA) and Sheng-Chien Lee (University of Florida, USA)
Copyright: 2006
Pages: 4
Source title: Emerging Trends and Challenges in Information Technology Management
Source Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-59904-019-6.ch067
ISBN13: 9781616921286
EISBN13: 9781466665361

Abstract

Using Internet-enabled mobile handheld devices to accessing the World Wide Web is a promising addition to the Web and traditional ecommerce. Mobile handheld devices provide convenience and portable access to the huge information on the Internet for mobile users from anywhere and at anytime. On the other hand, the traditional Web pages are mainly designed for viewing on desktop or notebook computers. They usually do not suit the devices well because the pages, especially the large text files, can not be properly, speedily displayed on the microbrowsers due to the limit of screen size, narrow network bandwidth, small memory capacity, and low computing power. This research investigates a method for large text summarization for mobile handheld devices. This method applies a Web usage mining technology—Web navigation pattern discovery and applications—to adaptive mobile Web browsing. An experimental example is given. Other related issues such as mobile commerce systems will also be discussed in this research.

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