Abstract
Users return to Web pages for various reasons. Apart from pages visited due to backtracking, users typically monitor a number of favorite pages, while dealing with tasks that reoccur on an infrequent basis. In this paper, we introduce a novel method for predicting the next revisited page in a certain user context that, unlike existing methods, doesn’t rely on machine learning algorithms. We evaluate it over a large data set comprising the navigational activity of 25 users over a period of 6 months. The outcomes suggest a significant improvement over methods typically used in this context, thus paving the way for exploring new means of improving user’s navigational support.
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