Collaborative Filtering Recommendation Algorithm Based on Sparse Bilinear Convolution

Authors

  • Xiangfeng Zhang Department of Information Engineering, Yellow River Conservancy Technical Institute, Kaifeng 475004, China

Abstract

 

In the process of personalized dynamic web page tag information detection, the amount of data errors caused by the disturbance of the fuzzy state feature is quite high. A personalized dynamic web page tag information collaborative filtering recommendation algorithm based on sparse bilinear convolution is proposed. The sparse bilinear convolution feature reconstruction method is adopted for the feature reconstruction of personalized dynamic web page tag information, the non-linear state information optimization analysis method is combined for regression analysis and point cloud structure reorganization of personalized dynamic web page tag information, the combined feature quantity of personalized dynamic web page tag information is extracted, the average mutual information feature quantity of personalized dynamic web page tag information is then extracted by feature extraction technology. Combined with the association rule mining method, the principal component analysis of personalized dynamic web page tag information is carried out, the similarity attribute category component of personalized dynamic web page tag information is mined, and the depth learning method is adopted to carry out adaptive optimization in the collaborative filtering recommendation process of personalized dynamic web page tag information, thus realizing a collaborative filtering recommendation of personalized dynamic web page tag information. The simulation results show that the attribute classification and identification of personalized dynamic web page tag information using this method are better, the feature resolution ability is stronger, and the intelligent recommendation ability of a personalized dynamic web page is improved.

Keywords: Thinning; Bilinear convolution; Collaborative filtering; Recommendation

Cite As

X. Zhang, “Collaborative Filtering Recommendation Algorithm Based on Sparse Bilinear Convolutionâ€,
Engineering Intelligent Systems, vol. 28 no. 4, pp. 205-214, 2020.




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Published

2020-12-01

Issue

Vol. 28 No. 4 (2020): International Journal of Engineering Intelligent Systems

Section

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