Web recommendation based on back propagation neural networks

Authors:
Jiang Zhong;Shitao Deng;Yifeng Cheng
Affiliations:
College of Computer Science, Chongqing University, Chongqing, China;College of Computer Science, Chongqing University, Chongqing, China;College of Computer Science, Chongqing University, Chongqing, China
Venue:
ISNN'11 Proceedings of the 8th international conference on Advances in neural networks - Volume Part III
Year:
2011

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Abstract

Back Propagation Neural Networks are simple, effective, robust and great to estimate predication model, which can be used to combine the latent and extenal features of users and web page for web recommendation.This paper propose a unified collaborative filtering model to get more accuracy recommendation. To discover user communities and prototypical interest profiles, Probabilistic Latent Semantic Analysis Model is applied.The experiment result shows that the technique are the higher accuracy, constant time prediction, and an explicit and compact model representation in the users' Web access log and users' basic information respectively.