RetaGNN: Relational temporal attentive graph neural networks for holistic sequential recommendation

Cheng Hsu, Cheng Te Li

研究成果: Conference contribution

45 引文 斯高帕斯(Scopus)

摘要

Sequential recommendation (SR) is to accurately recommend a list of items for a user based on her current accessed ones. While new-coming users continuously arrive in the real world, one crucial task is to have inductive SR that can produce embeddings of users and items without re-training. Given user-item interactions can be extremely sparse, another critical task is to have transferable SR that can transfer the knowledge derived from one domain with rich data to another domain. In this work, we aim to present the holistic SR that simultaneously accommodates conventional, inductive, and transferable settings. We propose a novel deep learning-based model, Relational Temporal Attentive Graph Neural Networks (RetaGNN), for holistic SR. The main idea of RetaGNN is three-fold. First, to have inductive and transferable capabilities, we train a relational attentive GNN on the local subgraph extracted from a user-item pair, in which the learnable weight matrices are on various relations among users, items, and attributes, rather than nodes or edges. Second, long-term and short-term temporal patterns of user preferences are encoded by a proposed sequential self-attention mechanism. Third, a relation-aware regularization term is devised for better training of RetaGNN. Experiments conducted on MovieLens, Instagram, and Book-Crossing datasets exhibit that RetaGNN can outperform state-of-the-art methods under conventional, inductive, and transferable settings. The derived attention weights also bring model explainability.

原文English
主出版物標題The Web Conference 2021 - Proceedings of the World Wide Web Conference, WWW 2021
發行者Association for Computing Machinery, Inc
頁面2968-2979
頁數12
ISBN(電子)9781450383127
DOIs
出版狀態Published - 2021 4月 19
事件2021 World Wide Web Conference, WWW 2021 - Ljubljana, Slovenia
持續時間: 2021 4月 192021 4月 23

出版系列

名字The Web Conference 2021 - Proceedings of the World Wide Web Conference, WWW 2021

Conference

Conference2021 World Wide Web Conference, WWW 2021
國家/地區Slovenia
城市Ljubljana
期間21-04-1921-04-23

All Science Journal Classification (ASJC) codes

  • 電腦網路與通信
  • 軟體

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