5G marketing system based on multi-sensor collaborative filtering algorithm

Ziyang Li

doi:10.1117/12.2641533

4 August 2022 5G marketing system based on multi-sensor collaborative filtering algorithm

Ziyang Li

Proceedings Volume 12306, Second International Conference on Digital Signal and Computer Communications (DSCC 2022); 123060R (2022) https://doi.org/10.1117/12.2641533
Event: Second International Conference on Digital Signal and Computer Communications (DSCC 2022), 2022, Changchun, China

Abstract

Massive user interaction information provides more data choices for recommender systems. With the increase of user choices, the sparsity of user interaction data has become an important challenge. For traditional recommendation algorithms, how to extract effective features to solve the problem of data sparsity has always been a hot research direction in the field of recommendation systems. In view of the above-mentioned problems, this paper proposes a recommender based on enhanced collaborative filtering algorithm for 5G marketing system. Specifically, by broadening the input vector field and fusing the user's social information and personal interaction information, the problem of multisource information collaborative modeling is effectively solved. Further, in order to achieve the enhancement of vector structure, we introduce a social regularization term and an internal regularization term to alleviate the overfitting problem of most recommendation algorithms. Experiments on a large number of real-world datasets show that our proposed method effectively improves the performance of the model on sparse data.

Citation Download Citation

Ziyang Li "5G marketing system based on multi-sensor collaborative filtering algorithm", Proc. SPIE 12306, Second International Conference on Digital Signal and Computer Communications (DSCC 2022), 123060R (4 August 2022); https://doi.org/10.1117/12.2641533

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