Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Predicting navigation patterns on the mobile-internet using time of the week
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
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Many systems use past behavior, preferences and environmental factors to attempt to predict user navigation on the Internet. However 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. Here we investigate an environmental factor, namely time, in making predictions about user navigation. We present methods for creating temporal rules that describe user navigation patterns. We also show the benefit of using these rules to predict user navigation and also 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.