User Analysis Based on Fuzzy Clustering
Ming Yang, Hong Li · 2009
In order to solve the problem of user-classification to reflect the features of Web users inflexible, a novel user classification model was presented in this paper. By introducing the concept of time discretization and applying fuzzy equivalence relation clustering to classify Web users, the model can rationally solve the user classification problems. Empirical results showed that the output of user classification was not unique and the parameter delta should be adjusted based on applications. Compared to those hard clustering, this model is proved to be more effective to classify web users.