Clustering analysis was carried out on the users interests is of great significance to the study of consumer psychology.Considering users interests is a kind of classification optimization clustering model

improve the users interests using the algorithm of ID3decision tree classification calculation speed

the attribute of the highest information gain as the test attributes of nodes before

to ensure the result of decomposition users interested in samples required minimum amount of information

building user interest classification optimization of adaptive fuzzy clustering objective function

the update matrix clustering prototype

under adaptive fuzzy clustering model

clustering prototype iterative equation is given directly

guarantee the accuracy of the classification.Experiment result shows that the proposed model is compared with traditional clustering model is not easy to fall into local optimal solution

has higher recall ratio and precision

and has great significance for further user behavior research.