Web Users Access Mode Mining Based on Quantum Self-organizing Neural Network

Proposed a model of web users access mode mining based on quantum self-organizing neural network, solved a variety of interest problems of web users mining, utilized related superposition features of quantum states, performed the operations of automatic classification and statistical analysis, output some neurons whose membership grade is greater than threshold value. Experimental results show that the designed model is feasible, has stronger model generalization ability and the generalization ability in the case of sufficient training samples, can better perform clustering operations for web users, dynamically generate personalized web pages for different classes web users.