Personalized Commodity Recommendation Method Based on Behavioral Delay Sharing Network

Hongxia ZHANG; Yanhui DONG; Junbi XIAO; Yongjin YANG

doi:10.11999/JEIT200964

Volume 43 Issue 10

Oct. 2021

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Hongxia ZHANG, Yanhui DONG, Junbi XIAO, Yongjin YANG. Personalized Commodity Recommendation Method Based on Behavioral Delay Sharing Network[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2993-3000. doi: 10.11999/JEIT200964

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Hongxia ZHANG, Yanhui DONG, Junbi XIAO, Yongjin YANG. Personalized Commodity Recommendation Method Based on Behavioral Delay Sharing Network[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2993-3000. doi: 10.11999/JEIT200964

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Personalized Commodity Recommendation Method Based on Behavioral Delay Sharing Network

doi: 10.11999/JEIT200964

College Computer Science and Technology, China University of Petroleum (East China), Qingdao 266580, China

Funds: The National Key Research and Development Project(2018YFC1406204), The National Natural Science Foundation of China (61872385), The Fundamental Research Funds for the Central University (18CX02140A)

Received Date: 2020-11-09
Rev Recd Date: 2021-06-28

Available Online: 2021-08-09

Publish Date: 2021-10-18

Abstract

Abstract

This paper proposes a Behavior Delayed Sharing Network (BDSN) model to solve the personalized product recommendation problem based on personal historical browsing behaviors. First, a Behavior Delay Gated Recurrent Neural Unit (BDGRU) is presented, which uses the historical browsing time interval as a user activity factor, and updates the neuron state to calculate the user's interest expression. Then, a shared parameter network is proposed to converge the representation vectors on the user side and the goods side into a unified space. Experiments show that the AUC index and loss function of BDSN model on the validation set are both optimal, and the AUC index on the test set increases by 37% compared with the basic model.
- Recommendation system,
- Sharing network,
- User activity,
- Click-through rate estimation,
- Gated Recurrent Unit (GRU)

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References(24)

References

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