スペクトル観点から効果的かつ効率的な個人推薦に向けて

• Material Type: 博士論文
• Title: スペクトル観点から効果的かつ効率的な個人推薦に向けて
• Author/Editor: Peng, Shaowen
• Author Heading: Peng, Shaowen
• Publication, Distribution, etc.: Kyoto University
• Publication Date: 2024-03-25
• Publication Date (W3CDTF): 2024-03-25
• Alternative Title: Towards Effective and Efficient Personalized Recommendation from a Spectral Perspective
• Contributor: 伊藤, 孝行; 田島, 敬史; 鹿島, 久嗣; 杉山, 一成
• Degree grantor/type: 京都大学
• Date Granted: 2024-03-25
• Dissertation Number: 甲第25430号
• Degree Type: 博士(情報学); Doctor of Informatics
• Text Language Code: eng
• Subject Heading: Information Retrieval; Recommender System; Collaborative Filtering; Graph Neural Network; Spectrum
• NDC: 007
• Target Audience: 一般
• DOI: 10.14989/doctor.k25430
• Format (IMT): application/pdf
• Access Restrictions: インターネット公開
• Rights (production): Peng S, Sugiyama K, Mine T. Less is more: reweighting important spectral graph features for recommendation[C]//Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2022: 1273-1282. https://dl.acm.org/doi/10.1145/3477495.3532014 Peng S, Sugiyama K, Mine T. SVD-GCN: A simplified graph convolution paradigm for recommendation[C]//Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 2022: 1625-1634. https://dl.acm.org/doi/10.1145/3511808.3557462 Peng S, Sugiyama K, Mine T. Less is More: Removing Redundancy of Graph Convolutional Networks for Recommendation[J]. ACM Transactions on Information Systems, 2024, 42(3): 1-26. https://dl.acm.org/doi/full/10.1145/3632751
• Data Provider (Database): 国立情報学研究所 : 学術機関リポジトリデータベース（IRDB）（機関リポジトリ）; https://irdb.nii.ac.jp
• Original Data Provider (Database): 京都大学 : 京都大学学術情報リポジトリ

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