• Park R, Pande A, Relyea D, Chennu P and Kanmanth Reddy P. SLH-BIA: Short-Long Hawkes Process for Buy It Again Recommendations at Scale. Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval. (2965-2969).

    https://doi.org/10.1145/3626772.3661374

  • Zhang K, Chu D, Tu Z, Liu X and Zhang B. (2024). LSTM-UBI: a user behavior inertia based recommendation method. Multimedia Tools and Applications. 10.1007/s11042-024-18256-2. 83:27. (69227-69248).

    https://link.springer.com/10.1007/s11042-024-18256-2

  • Li W, Zhang C, Zhou X and Jin Q. (2023). Dynamic Multi-view Group Preference Learning for group behavior prediction in social networks. Expert Systems with Applications. 10.1016/j.eswa.2023.120553. 231. (120553). Online publication date: 1-Nov-2023.

    https://linkinghub.elsevier.com/retrieve/pii/S0957417423010552

  • Ding H, Kveton B, Ma Y, Park Y, Kini V, Gu Y, Divvela R, Wang F, Deoras A and Wang H. Trending Now: Modeling Trend Recommendations. Proceedings of the 17th ACM Conference on Recommender Systems. (294-305).

    https://doi.org/10.1145/3604915.3608810

  • Huang C, Wang S, Wang X and Yao L. Modeling Temporal Positive and Negative Excitation for Sequential Recommendation. Proceedings of the ACM Web Conference 2023. (1252-1263).

    https://doi.org/10.1145/3543507.3583463

  • Chu Z, Wang H, Xiao Y, Long B and Wu L. Meta Policy Learning for Cold-Start Conversational Recommendation. Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining. (222-230).

    https://doi.org/10.1145/3539597.3570443

  • Wang D, Zhang X, Xiang Z, Yu D, Xu G and Deng S. Sequential Recommendation Based on Multivariate Hawkes Process Embedding With Attention. IEEE Transactions on Cybernetics. 10.1109/TCYB.2021.3077361. 52:11. (11893-11905).

    https://ieeexplore.ieee.org/document/9447892/

  • Wang P, Cai R and Wang H. Graph-based Extractive Explainer for Recommendations. Proceedings of the ACM Web Conference 2022. (2163-2171).

    https://doi.org/10.1145/3485447.3512168

  • Jiang Y, Liu G, Wu J and Lin H. Telecom Fraud Detection via Hawkes-enhanced Sequence Model. IEEE Transactions on Knowledge and Data Engineering. 10.1109/TKDE.2022.3150803. (1-1).

    https://ieeexplore.ieee.org/document/9712421/

  • Li Y, Ding Y, Chen B, Xin X, Wang Y, Shi Y, Tang R and Wang D. Extracting Attentive Social Temporal Excitation for Sequential Recommendation. Proceedings of the 30th ACM International Conference on Information & Knowledge Management. (998-1007).

    https://doi.org/10.1145/3459637.3482257

  • Micol Policarpo L, da Silveira D, da Rosa Righi R, Antunes Stoffel R, da Costa C, Victória Barbosa J, Scorsatto R and Arcot T. (2021). Machine learning through the lens of e-commerce initiatives. Computer Science Review. 41:C. Online publication date: 1-Aug-2021.

    https://doi.org/10.1016/j.cosrev.2021.100414

  • Cai R, Wu J, San A, Wang C and Wang H. Category-aware Collaborative Sequential Recommendation. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval. (388-397).

    https://doi.org/10.1145/3404835.3462832

  • Deshpande P, Marathe K, De A and Sarawagi S. Long Horizon Forecasting with Temporal Point Processes. Proceedings of the 14th ACM International Conference on Web Search and Data Mining. (571-579).

    https://doi.org/10.1145/3437963.3441740

  • Wu J, Cai R and Wang H. Déjà vu: A Contextualized Temporal Attention Mechanism for Sequential Recommendation. Proceedings of The Web Conference 2020. (2199-2209).

    https://doi.org/10.1145/3366423.3380285

  • Ma J, Zhao P, Liu Y, Sheng V, Xu J and Zhao L. (2020). Modeling Periodic Pattern with Self-Attention Network for Sequential Recommendation. Database Systems for Advanced Applications. 10.1007/978-3-030-59419-0_34. (557-572).

    http://link.springer.com/10.1007/978-3-030-59419-0_34

  • Chu Z, Cai R and Wang H. Accounting for Temporal Dynamics in Document Streams. Proceedings of the 28th ACM International Conference on Information and Knowledge Management. (1813-1822).

    https://doi.org/10.1145/3357384.3358022

  • Wang C, Zhang M, Ma W, Liu Y and Ma S. Modeling Item-Specific Temporal Dynamics of Repeat Consumption for Recommender Systems. The World Wide Web Conference. (1977-1987).

    https://doi.org/10.1145/3308558.3313594