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RippleNet.pptx

发布时间：2022-05-31 发布人：admin 分类：说明书 资料大小：5.43M 资料格式：pptx 举报 版权申诉
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    Authors:Hongwei Wang, Fuzheng Zhang, Jialin Wang, Miao Zhao, WenjieLi, Xing Xie, Minyi Guo Venue : CIKM 2018 Presenter : JIARUI CHEN (201700301042)
    Outline • Introduction • Motivation • Method • Dataset • Experiment • Conclusion 2
    Introduction · Recommendation System · Information overload. · Brother of Search Engine. · Categories. 3
    Introduction · Knowledge Graph · Heterogeneous network. · Node -> Entity,Edge -> Relation. · Example. 4
    Introduction · Knowledge Graph based Recommendation · Heterogeneous network. · Node -> Entity,Edge -> Relation. · Example. 5
    Introduction · Knowledge Graph based Recommendation · Heterogeneous network. · Node -> Entity,Edge -> Relation. Knowledge Graph Layer User Layer 6
    Motivation · Existing Works · Embedding-based methods : · Use knowledge graph embedding to incorporates the learned entity embeddings into a recommendation framework. · These models more suitable for a graph tasks (e.g. link prediction) than recommendation. · Path-based methods : · Explore the various pattern of connections among items in KG to provide additional guidance for recommendations, e.g.through Meta-path. · Rely heavily on manually designed meta-paths,which is hard to optimize in practice. 7
    Motivation · Key Idea : Preference propagation as ripples on the water · Combine above two categories together. · Use the items in the ripple sets as side information. · Example. 8
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