{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/graph-convolutional-matrix-completion","title":"Graph Convolutional Matrix Completion","arxiv_id":"1706.02263","date":"2017-06-07","proceeding":null,"authors":["Rianne van den Berg","Thomas N. Kipf","Max Welling"],"abstract":"We consider matrix completion for recommender systems from the point of view\nof link prediction on graphs. Interaction data such as movie ratings can be\nrepresented by a bipartite user-item graph with labeled edges denoting observed\nratings. Building on recent progress in deep learning on graph-structured data,\nwe propose a graph auto-encoder framework based on differentiable message\npassing on the bipartite interaction graph. Our model shows competitive\nperformance on standard collaborative filtering benchmarks. In settings where\ncomplimentary feature information or structured data such as a social network\nis available, our framework outperforms recent state-of-the-art methods.","url_abs":"http://arxiv.org/abs/1706.02263v2","url_pdf":"http://arxiv.org/pdf/1706.02263v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/riannevdberg/gc-mc","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/OweysMomenzada/Graph-Neural-Networks-for-effecient-Recommender-Systems","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/blueghostyi/id-grec","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/hengruizhang98/GCMC-Pytorch-dgl","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/lmcRS/AWS-recommendation-papers","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/paryanasr/HonoursProject-Recommender-System-gc-mc","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/swtheing/Multiview-Link-Representation-Learning","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/tanimutomo/gcmc","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/tjcdev/gcmc-tf2","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/tobiasweede/rs-via-gnn","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/tubamuzzaffar/g","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/tubamuzzaffar/gc","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/tubamuzzaffar/gc2","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/tubamuzzaffar/gcmc-2","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/xiaoleiHou214/gc-mc-master","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/PreferredAI/cornac","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"tf","reach":{"status":"ok","spdx":"Apache-2.0"}},{"paper_slug":"graph-convolutional-matrix-completion","repo_url":"https://github.com/dmlc/dgl/tree/master/examples/mxnet/_deprecated/gcmc","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"collaborative-filtering","task_name":"Collaborative Filtering"},{"task_slug":"link-prediction","task_name":"Link Prediction"},{"task_slug":"matrix-completion","task_name":"Matrix Completion"},{"task_slug":"recommendation-systems","task_name":"Recommendation Systems"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/recommendation-systems-on-douban-monti","task":"Recommendation Systems","dataset":"Douban Monti","model":"GC-MC","rank_in_archive_order":5,"of":8,"metrics":{"RMSE":"0.734"},"uses_additional_data":true},{"leaderboard":"/sota/recommendation-systems-on-flixster-monti","task":"Recommendation Systems","dataset":"Flixster Monti","model":"GC-MC","rank_in_archive_order":5,"of":7,"metrics":{"RMSE":"0.917"},"uses_additional_data":true},{"leaderboard":"/sota/collaborative-filtering-on-movielens-100k","task":"Recommendation Systems","dataset":"MovieLens 100K","model":"GC-MC","rank_in_archive_order":8,"of":18,"metrics":{"RMSE (u1 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