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Journal

  1. Yuma Dose, Shuichiro Haruta, Takahiro Hara, "INCL: A Graph-based Recommendation Model Using Contrastive Learning for Inductive Scenario," 情報処理学会 論文誌 (IPSJ Journal), vol.65, no.11, pp.1-9, November 2024.

International Conference

  1. Kentaro Shiga, Shuichiro Haruta, Zhi Li, Takahiro Hara, "Domain Adaptation Utilizing Texts and Visions for Cross-domain Recommendations with No Shared Users," Proceedings of IEEE International Conference on Machine Learning and Applications (ICMLA), December 2024.
  2. Yuma Dose, Shuichiro Haruta, Yihong Zhang, Takahiro Hara, "Hypergraph Contrastive Learning with Graph Structure Learning for Recommendation," Proceedings of IEEE International Conference on Machine Learning and Applications (ICMLA), December 2024.
  3. Zhi Li, Daichi Amagata, Yihong Zhang, Takahiro Hara, Shuichiro Haruta, Kei Yonekawa, Mori Kurokawa, "Mutual Information-based Preference Disentangling and Transferring for Non-overlapped Multi-target Cross-domain Recommendations," Proceedings of International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), July 2024.
  4. Rikuto Tsubouchi, Takahiro Hara, Kei Yonekawa, Shuichiro Haruta, "Unvisited Out-Of-Town POI Recommendation with Simultaneous Learning of Multiple Regions.," Proceedings of IEEE International Conference on Big Data (BigData), pp.915-924, December 2023.
  5. Yuma Dose, Shuichiro Haruta, Takahiro Hara, "A Graph-Based Recommendation Model Using Contrastive Learning for Inductive Scenario," Proceedings of IEEE International Conference on Machine Learning and Applications (ICMLA), December 2023.
  6. Zhi Li, Daichi Amagata, Yihong Zhang, Takahiro Hara, Shuichiro Haruta, Kei Yonekawa, Mori Kurokawa, "Semantic Relation Transfer for Non-overlapped Cross-domain Recommendations," The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), vol.13937, pp.271-283, May 2023.
  7. Zhi Li, Daichi Amagata, Yihong Zhang, Takahiro Hara, Shuichiro Haruta, Kei Yonekawa, Mori Kurokawa, "Debiasing Graph Transfer Learning via Item Semantic Clustering for Cross-Domain Recommendations.," Proceedings of IEEE International Conference on Big Data (BigData), pp.762-769, December 2022.

Domestic Conference

  1. 前川 由幸, 春田 秀一郎, 道瀬 悠磨, 原 隆浩, "ChatGPT による読者像と記事カテゴリの推定を用いたニュース推薦フレームワーク," 情報処理学会 マルチメディア, 分散, 協調とモバイル シンポジウム (DICOMO), 2024年6月.
  2. 道瀬 悠磨, 春田 秀一郎, 原 隆浩, "対照学習およびグラフ構造学習を用いた ハイパーグラフベース推薦モデル," 情報処理学会 マルチメディア, 分散, 協調とモバイル シンポジウム (DICOMO), 2024年6月.
  3. 道瀬 悠磨, 春田 秀一郎, 原 隆浩, "対照学習を用いたノードの追加に頑強なグラフベース推薦モデル," 情報処理学会 マルチメディア, 分散, 協調とモバイル シンポジウム (DICOMO), 2023年7月.
  4. 壺内 陸友, 原 隆浩, 米川 慧, 春田 秀一郎, "複数地域の同時学習が可能な未訪問Out-Of-Town POI 推薦手法," データ工学と情報マネジメントに関するフォーラム (DEIM), 2023年3月.

Award

  1. 道瀬 悠磨, 春田 秀一郎, 原 隆浩, "最優秀論文賞," 情報処理学会 マルチメディア, 分散, 協調とモバイル シンポジウム , 2023年7月.
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