Preference-function algorithm : A novel approach for selection of the users' preferred websites
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 328-346 |
Journal / Publication | International Journal of Business Intelligence and Data Mining |
Volume | 2 |
Issue number | 3 |
Publication status | Published - Oct 2007 |
Link(s)
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. © 2007, Inderscience Publishers.
Research Area(s)
- Classification, Clustering, Customisation, Pattern discovery, Personalisation, Usage mining, Web mining
Citation Format(s)
Preference-function algorithm: A novel approach for selection of the users' preferred websites. / Makki, S. Kami; Jani, Seema; Jia, Xiaohua et al.
In: International Journal of Business Intelligence and Data Mining, Vol. 2, No. 3, 10.2007, p. 328-346.
In: International Journal of Business Intelligence and Data Mining, Vol. 2, No. 3, 10.2007, p. 328-346.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review