An empirical comparison of four initialization methods for the K-Means algorithm
Pattern Recognition Letters
Concept decompositions for large sparse text data using clustering
Machine Learning
Learning implicit user interest hierarchy for context in personalization
Proceedings of the 8th international conference on Intelligent user interfaces
IEEE Internet Computing
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This paper proposes a system for finding a user’s interests on the Internet. It is based on his browsing behaviors and the contents of his visited pages. The system has two features. One is building user’s browsing interests implicitly, multiple keyword vectors, one per interest. The other is that it can generate interests by selecting different time periods. Dynamical generation can adapt to the change of user interests. Experiments show that most of generated interests are matched to user’s real interests. The system finds their interests automatically and dynamically.