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Web Intelligence, IEEE / WIC / ACM International Conference on (2005)
Compi?gne University of Technology, France
Sept. 19, 2005 to Sept. 22, 2005
ISBN: 0-7695-2415-X
pp: 636-640
There are many systems that attempt to predict user navigation on the Internet through the use of past behavior, preferences and environmental factors. We believe that many of these models have shortcomings, in that they do not take into account that users may have many different sets of preferences, specifically, we investigate time as an environmental factor in making predictions about user navigation. We present a method for segmenting log files in order to learn time dependent models to predict user navigation patterns and show the benefits of these models over traditional methods. An analysis is carried out on a sample of usage logs for Wireless Application Protocol (WAP) browsing, and the results of this analysis verify our hypothesis.
Barry Smyth, Martin Halvey, Mark T. Keane, "Time Based Segmentation of Log Data for User Navigation Prediction in Personalization", Web Intelligence, IEEE / WIC / ACM International Conference on, vol. 00, no. , pp. 636-640, 2005, doi:10.1109/WI.2005.147
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