TIAE-DSIN: A time interval aware deep session interest network for click-through rate prediction
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Published:2024-09
Issue:
Volume:249
Page:123531
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ISSN:0957-4174
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Container-title:Expert Systems with Applications
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language:en
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Short-container-title:Expert Systems with Applications
Author:
Zhang Chunxue,
Qiu LiqingORCID,
Jing Caixia,
Sun Cheng'ai
Reference31 articles.
1. STF-RNN: Space time features-based recurrent neural network for predicting people next location;Al-Molegi,2016
2. Feng Y., Lv F., Shen W., Wang M., Sun F., Zhu Y., Yang K. (2019). Deep session interest network for click-through rate prediction. arXiv preprint arXiv:1905.06482.
3. Grbovic M., Cheng H. (2018). Real-time personalization using embeddings for search ranking at airbnb. InProceedings of the 24th ACM SIGKDD international conference on knowledge discovery & data mining. (pp. 311-320).
4. Guo H., Tang R., Ye Y., Li Z., He X. (2017). DeepFM: a factorization-machine based neural network for CTR prediction. arXiv preprint arXiv:1703.04247.
5. Hu, H., He, X., Gao, J., & Zhang, Z. L. (2020). Modeling personalized item frequency information for next-basket recommendation. In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 1071-1080).