Multi-level cross-view contrastive learning for knowledge-aware recommender system

• المؤلفون الرئيسيون: ZOU, Ding, WEI, Wei, MAO, Xian-Ling, WANG, Ziyang, QIU, Minghui, ZHU, Feida, CAO, Xin
• التنسيق: text
• اللغة: English
• منشور في: Institutional Knowledge at Singapore Management University 2022
• الموضوعات: contrastive learning; graph neural network; knowledge graph; multi-view graph learning; recommender system; Artificial Intelligence and Robotics; Databases and Information Systems
• الوصول للمادة أونلاين: https://ink.library.smu.edu.sg/sis_research/7228; https://ink.library.smu.edu.sg/context/sis_research/article/8231/viewcontent/Multi_levelCross_view_SIGIR_2022_av.pdf

Knowledge graph (KG) plays an increasingly important role in recommender systems. Recently, graph neural networks (GNNs) based model has gradually become the theme of knowledge-aware recommendation (KGR). However, there is a natural deficiency for GNN-based KGR models, that is, the sparse supervised...