Classification Optimization Clustering Model Simulation Based on User Interest

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