Abstract
Recommendation system is one of the most important service applications in the world, and graph neural network is currently the most popular research direction in the field of recommendation system. In this survey, we conduct a literature survey on graph neural network-based recommender systems. Firstly, we introduce the classification for graph neural networks. Secondly, different recommendation scenarios in the recommendation system are introduced, and the challenges faced by graph neural networks in different recommendation scenarios are analyzed. Finally, the solutions to these challenges are summarized.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.