Feb. 2, 2024, 3:45 p.m. | Maolin Wang Yu Pan Zenglin Xu Ruocheng Guo Xiangyu Zhao Wanyu Wang Yiqi Wang Zitao Liu

cs.LG updates on arXiv.org arxiv.org

Temporal Point Processes (TPPs) hold a pivotal role in modeling event sequences across diverse domains, including social networking and e-commerce, and have significantly contributed to the advancement of recommendation systems and information retrieval strategies. Through the analysis of events such as user interactions and transactions, TPPs offer valuable insights into behavioral patterns, facilitating the prediction of future trends. However, accurately forecasting future events remains a formidable challenge due to the intricate nature of these patterns. The integration of Neural Networks …

advancement analysis commerce contributed cs.ai cs.lg distribution diverse domains e-commerce event events function general information insights interactions modeling networking patterns pivotal processes recommendation recommendation systems retrieval role social social networking stat.ml strategies systems temporal through transactions

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