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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 ID3 decision 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.