Webpage Recommendation Model in Personalized Service based on the Group Clustering

摘要

This paper proposes an effective model to realize the Webpage recommendation in personalized service based on the data mining technology. Applying user interest feature vector and user session feature vector to represents user's interest and generate user groups' interests by clustering, and extends the individual user interest. The experiment proves that the model is effective and accuracy.