Abstract
With the rapid development of e-commerce, the importance of mining and predicting user's navigation patterns grows larger than before. As an important task of Web usage mining, mining users' navigation patterns is the fundamental approach for generating recommendations. But the user interests are changeable, and it is difficult to track the exact user navigation patterns. In this paper, we propose an ant colony approach for this problem. In our approach, we consider the web users as artificial ants, and use the ant colony behavior as a metaphor to guide user's choice in the Web site. Firstly, a user navigation model is built, based on ant colony behavior and Web logs. Secondly, we design an algorithm for mining users interest navigation patterns dynamically. The experimental results proved the effectiveness of our approach.
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