Title: Preference-Function Algorithm: a novel approach for selection of the users' preferred websites

Authors: S. Kami Makki, Seema Jani, Xiaohua Jia, Wuxu Peng

Addresses: Department of Electrical Engineering and Computer Science, College of Engineering, University of Toledo, 2801 W. Bancroft St., Toledo, Ohio 43606, USA. ' Department of Electrical Engineering and Computer Science, College of Engineering, University of Toledo, 2801 W. Bancroft St., Toledo, Ohio 43606, USA. ' Department of Computer Science, City University of Hong Kong, 83 Tat Chee Ave, Kowloon, Hong Kong. ' Department of Computer Science, Texas State University, San Marcos, TX 78666, USA

Abstract: Designing a website which is helpful to its users requires knowledge of the users| preferences and their motivations. Therefore, a designer requires to anticipate the users| needs and structures the website accordingly. This paper implements a novel approach for selecting the users| preferred web pages. In this approach, the navigated web pages are modelled as a finite state graph, where each visited web page is defined as a state. This graph then is used to provide the framework for determining the users| interest. The viability of this approach is demonstrated with a user-created website scenario.

Keywords: web mining; clustering; classification; personalisation; customisation; usage mining; pattern discovery; user preferences; preferred websites; website selection; website design; web pages; data mining.

DOI: 10.1504/IJBIDM.2007.015488

International Journal of Business Intelligence and Data Mining, 2007 Vol.2 No.3, pp.328 - 346

Available online: 19 Oct 2007 *

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