Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81232
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Title: Graph neural networks for social recommendation
Authors: Fan, W
Ma, Y
Li, Q 
He, Y
Zhao, E
Tang, J
Yin, D
Issue Date: 2019
Source: The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019, 2019, p. 417-426
Abstract: In recent years, Graph Neural Networks (GNNs), which can naturally integrate node information and topological structure, have been demonstrated to be powerful in learning on graph data. These advantages of GNNs provide great potential to advance social recommendation since data in social recommender systems can be represented as user-user social graph and user-item graph; and learning latent factors of users and items is the key. However, building social recommender systems based on GNNs faces challenges. For example, the user-item graph encodes both interactions and their associated opinions; social relations have heterogeneous strengths; users involve in two graphs (e.g., the user-user social graph and the user-item graph). To address the three aforementioned challenges simultaneously, in this paper, we present a novel graph neural network framework (GraphRec) for social recommendations. In particular, we provide a principled approach to jointly capture interactions and opinions in the user-item graph and propose the framework GraphRec, which coherently models two graphs and heterogeneous strengths. Extensive experiments on two real-world datasets demonstrate the effectiveness of the proposed framework GraphRec.
Keywords: Graph neural networks
Neural networks
Recommender systems
Social network
Social recommendation
Publisher: Association for Computing Machinery, Inc
ISBN: 9781450366748
DOI: 10.1145/3308558.3313488
Description: 2019 World Wide Web Conference, WWW 2019, United States, 13-17 May 2019
Rights: © 2019 IW3C2 (International World Wide Web Conference Committee), published under Creative Commons CC-BY 4.0 License.
The following publication Fan, W., Ma, Y., Li, Q., He, Y., Zhao, E., Tang, J., & Yin, D. (2019, May). Graph Neural Networks for Social Recommendation. In The World Wide Web Conference (pp. 417-426). ACM, is available at https://doi.org/10.1145/3308558.3313488
Appears in Collections:Conference Paper

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