{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T05:13:45Z","timestamp":1755839625371,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":40,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T00:00:00Z","timestamp":1697846400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,10,21]]},"DOI":"10.1145\/3583780.3614917","type":"proceedings-article","created":{"date-parts":[[2023,10,21]],"date-time":"2023-10-21T07:45:26Z","timestamp":1697874326000},"page":"173-182","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["How Expressive are Graph Neural Networks in Recommendation?"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-5262-155X","authenticated-orcid":false,"given":"Xuheng","family":"Cai","sequence":"first","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0725-2211","authenticated-orcid":false,"given":"Lianghao","family":"Xia","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3332-1073","authenticated-orcid":false,"given":"Xubin","family":"Ren","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2062-1512","authenticated-orcid":false,"given":"Chao","family":"Huang","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]}],"member":"320","published-online":{"date-parts":[[2023,10,21]]},"reference":[{"key":"e_1_3_2_2_1_1","volume-title":"Martin Grohe, and Thomas Lukasiewicz.","author":"Abboud Ralph","year":"2020","unstructured":"Ralph Abboud , Ismail Ilkan Ceylan , Martin Grohe, and Thomas Lukasiewicz. 2020 . The surprising power of graph neural networks with random node initialization. arXiv preprint arXiv:2010.01179 (2020). Ralph Abboud, Ismail Ilkan Ceylan, Martin Grohe, and Thomas Lukasiewicz. 2020. The surprising power of graph neural networks with random node initialization. arXiv preprint arXiv:2010.01179 (2020)."},{"key":"e_1_3_2_2_2_1","volume-title":"Philippe Di Francesco, and Emmanuel Guitter","author":"Bouttier J\u00e9r\u00e9mie","year":"2003","unstructured":"J\u00e9r\u00e9mie Bouttier , Philippe Di Francesco, and Emmanuel Guitter . 2003 . Geodesic distance in planar graphs. Nuclear physics B, Vol. 663 , 3 (2003), 535--567. J\u00e9r\u00e9mie Bouttier, Philippe Di Francesco, and Emmanuel Guitter. 2003. Geodesic distance in planar graphs. Nuclear physics B, Vol. 663, 3 (2003), 535--567."},{"key":"e_1_3_2_2_3_1","volume-title":"LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation. arXiv preprint arXiv:2302.08191","author":"Cai Xuheng","year":"2023","unstructured":"Xuheng Cai , Chao Huang , Lianghao Xia , and Xubin Ren . 2023. LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation. arXiv preprint arXiv:2302.08191 ( 2023 ). Xuheng Cai, Chao Huang, Lianghao Xia, and Xubin Ren. 2023. LightGCL: Simple Yet Effective Graph Contrastive Learning for Recommendation. arXiv preprint arXiv:2302.08191 (2023)."},{"key":"e_1_3_2_2_4_1","volume-title":"Graph Neural Networks for Link Prediction with Subgraph Sketching. arXiv preprint arXiv:2209.15486","author":"Chamberlain Benjamin Paul","year":"2022","unstructured":"Benjamin Paul Chamberlain , Sergey Shirobokov , Emanuele Rossi , Fabrizio Frasca , Thomas Markovich , Nils Hammerla , Michael M Bronstein , and Max Hansmire . 2022. Graph Neural Networks for Link Prediction with Subgraph Sketching. arXiv preprint arXiv:2209.15486 ( 2022 ). Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Hammerla, Michael M Bronstein, and Max Hansmire. 2022. Graph Neural Networks for Link Prediction with Subgraph Sketching. arXiv preprint arXiv:2209.15486 (2022)."},{"key":"e_1_3_2_2_5_1","volume-title":"Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach. In AAAI Conference on Artificial Intelligence (AAAI)","volume":"34","author":"Chen Lei","year":"2020","unstructured":"Lei Chen , Le Wu , Richang Hong , Kun Zhang , and Meng Wang . 2020 . Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach. In AAAI Conference on Artificial Intelligence (AAAI) , Vol. 34 . 27--34. Lei Chen, Le Wu, Richang Hong, Kun Zhang, and Meng Wang. 2020. Revisiting Graph Based Collaborative Filtering: A Linear Residual Graph Convolutional Network Approach. In AAAI Conference on Artificial Intelligence (AAAI), Vol. 34. 27--34."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3434185"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3298689.3347058"},{"key":"e_1_3_2_2_8_1","volume-title":"IJCAI","volume":"2021","author":"Dacrema Maurizio Ferrari","year":"2020","unstructured":"Maurizio Ferrari Dacrema , Paolo Cremonesi , Dietmar Jannach , 2020 a. Methodological issues in recommender systems research . In IJCAI , Vol. 2021 . International Joint Conferences on Artificial Intelligence, 4706--4710. Maurizio Ferrari Dacrema, Paolo Cremonesi, Dietmar Jannach, et al. 2020a. Methodological issues in recommender systems research. In IJCAI, Vol. 2021. International Joint Conferences on Artificial Intelligence, 4706--4710."},{"key":"e_1_3_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3411901"},{"key":"e_1_3_2_2_10_1","volume-title":"Protein interface prediction using graph convolutional networks. Advances in neural information processing systems (NeurIPS)","author":"Fout Alex","year":"2017","unstructured":"Alex Fout , Jonathon Byrd , Basir Shariat , and Asa Ben-Hur . 2017. Protein interface prediction using graph convolutional networks. Advances in neural information processing systems (NeurIPS) , Vol. 30 ( 2017 ). Alex Fout, Jonathon Byrd, Basir Shariat, and Asa Ben-Hur. 2017. Protein interface prediction using graph convolutional networks. Advances in neural information processing systems (NeurIPS), Vol. 30 (2017)."},{"key":"e_1_3_2_2_11_1","volume-title":"International conference on machine learning (ICML). PMLR, 1263--1272","author":"Gilmer Justin","year":"2017","unstructured":"Justin Gilmer , Samuel S Schoenholz , Patrick F Riley , Oriol Vinyals , and George E Dahl . 2017 . Neural message passing for quantum chemistry . In International conference on machine learning (ICML). PMLR, 1263--1272 . Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl. 2017. Neural message passing for quantum chemistry. In International conference on machine learning (ICML). PMLR, 1263--1272."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3028705"},{"volume-title":"Graph theory","author":"Halary Frank","key":"e_1_3_2_2_13_1","unstructured":"Frank Halary . 1994. Graph theory . Addison-Wesley . Frank Halary. 1994. Graph theory. Addison-Wesley."},{"key":"e_1_3_2_2_14_1","volume-title":"Representation learning on graphs: Methods and applications. arXiv preprint arXiv:1709.05584","author":"Hamilton William L","year":"2017","unstructured":"William L Hamilton , Rex Ying , and Jure Leskovec . 2017. Representation learning on graphs: Methods and applications. arXiv preprint arXiv:1709.05584 ( 2017 ). William L Hamilton, Rex Ying, and Jure Leskovec. 2017. Representation learning on graphs: Methods and applications. arXiv preprint arXiv:1709.05584 (2017)."},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3397271.3401063"},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330760"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/30.1-2.81"},{"key":"e_1_3_2_2_18_1","volume-title":"Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907","author":"Kipf Thomas N","year":"2016","unstructured":"Thomas N Kipf and Max Welling . 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 ( 2016 ). Thomas N Kipf and Max Welling. 2016. Semi-supervised classification with graph convolutional networks. arXiv preprint arXiv:1609.02907 (2016)."},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.3390\/electronics11010141"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.263"},{"key":"e_1_3_2_2_21_1","volume-title":"Graph Transformer for Recommendation. arXiv preprint arXiv:2306.02330","author":"Li Chaoliu","year":"2023","unstructured":"Chaoliu Li , Lianghao Xia , Xubin Ren , Yaowen Ye , Yong Xu , and Chao Huang . 2023. Graph Transformer for Recommendation. arXiv preprint arXiv:2306.02330 ( 2023 ). Chaoliu Li, Lianghao Xia, Xubin Ren, Yaowen Ye, Yong Xu, and Chao Huang. 2023. Graph Transformer for Recommendation. arXiv preprint arXiv:2306.02330 (2023)."},{"key":"e_1_3_2_2_22_1","volume-title":"Disentangled Contrastive Collaborative Filtering. arXiv preprint arXiv:2305.02759","author":"Ren Xubin","year":"2023","unstructured":"Xubin Ren , Lianghao Xia , Jiashu Zhao , Dawei Yin , and Chao Huang . 2023. Disentangled Contrastive Collaborative Filtering. arXiv preprint arXiv:2305.02759 ( 2023 ). Xubin Ren, Lianghao Xia, Jiashu Zhao, Dawei Yin, and Chao Huang. 2023. Disentangled Contrastive Collaborative Filtering. arXiv preprint arXiv:2305.02759 (2023)."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611976700.38"},{"volume-title":"European semantic web conference","author":"Schlichtkrull Michael","key":"e_1_3_2_2_24_1","unstructured":"Michael Schlichtkrull , Thomas N Kipf , Peter Bloem , Rianne van den Berg , Ivan Titov , and Max Welling . 2018. Modeling relational data with graph convolutional networks . In European semantic web conference . Springer , 593--607. Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling. 2018. Modeling relational data with graph convolutional networks. In European semantic web conference. Springer, 593--607."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482264"},{"key":"e_1_3_2_2_26_1","volume-title":"Neural Graph Collaborative Filtering. In ACM SIGIR conference on Research and development in information retrieval (SIGIR).","author":"Wang Xiang","year":"2019","unstructured":"Xiang Wang , Xiangnan He , Meng Wang , Fuli Feng , and Tat-Seng Chua . 2019 . Neural Graph Collaborative Filtering. In ACM SIGIR conference on Research and development in information retrieval (SIGIR). Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, and Tat-Seng Chua. 2019. Neural Graph Collaborative Filtering. In ACM SIGIR conference on Research and development in information retrieval (SIGIR)."},{"key":"e_1_3_2_2_27_1","volume-title":"Multi-Modal Self-Supervised Learning for Recommendation. In The Web Conference (WWW). 790--800","author":"Wei Wei","year":"2023","unstructured":"Wei Wei , Chao Huang , Lianghao Xia , and Chuxu Zhang . 2023 . Multi-Modal Self-Supervised Learning for Recommendation. In The Web Conference (WWW). 790--800 . Wei Wei, Chao Huang, Lianghao Xia, and Chuxu Zhang. 2023. Multi-Modal Self-Supervised Learning for Recommendation. In The Web Conference (WWW). 790--800."},{"key":"e_1_3_2_2_28_1","first-page":"12","article-title":"The reduction of a graph to canonical form and the algebra which appears therein. nti","volume":"2","author":"Weisfeiler Boris","year":"1968","unstructured":"Boris Weisfeiler and Andrei Leman . 1968 . The reduction of a graph to canonical form and the algebra which appears therein. nti , Series , Vol. 2 , 9 (1968), 12 -- 16 . Boris Weisfeiler and Andrei Leman. 1968. The reduction of a graph to canonical form and the algebra which appears therein. nti, Series, Vol. 2, 9 (1968), 12--16.","journal-title":"Series"},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3404835.3462862"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485447.3512156"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1145\/3477495.3532058"},{"key":"e_1_3_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539473"},{"key":"e_1_3_2_2_33_1","volume-title":"How powerful are graph neural networks? arXiv preprint arXiv:1810.00826","author":"Xu Keyulu","year":"2018","unstructured":"Keyulu Xu , Weihua Hu , Jure Leskovec , and Stefanie Jegelka . 2018. How powerful are graph neural networks? arXiv preprint arXiv:1810.00826 ( 2018 ). Keyulu Xu, Weihua Hu, Jure Leskovec, and Stefanie Jegelka. 2018. How powerful are graph neural networks? arXiv preprint arXiv:1810.00826 (2018)."},{"key":"e_1_3_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219890"},{"key":"e_1_3_2_2_35_1","volume-title":"Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. In ACM Web Conference (WWW). 413--424","author":"Yu Junliang","year":"2021","unstructured":"Junliang Yu , Hongzhi Yin , Jundong Li , Qinyong Wang , Nguyen Quoc Viet Hung , and Xiangliang Zhang . 2021 . Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. In ACM Web Conference (WWW). 413--424 . Junliang Yu, Hongzhi Yin, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung, and Xiangliang Zhang. 2021. Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. In ACM Web Conference (WWW). 413--424."},{"key":"e_1_3_2_2_36_1","volume-title":"ACM SIGIR conference on Research and development in information retrieval (SIGIR). 1294--1303","author":"Yu Junliang","year":"2022","unstructured":"Junliang Yu , Hongzhi Yin , Xin Xia , Tong Chen , Lizhen Cui , and Quoc Viet Hung Nguyen . 2022 b. Are graph augmentations necessary? Simple graph contrastive learning for recommendation . In ACM SIGIR conference on Research and development in information retrieval (SIGIR). 1294--1303 . Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Lizhen Cui, and Quoc Viet Hung Nguyen. 2022b. Are graph augmentations necessary? Simple graph contrastive learning for recommendation. In ACM SIGIR conference on Research and development in information retrieval (SIGIR). 1294--1303."},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i8.20875"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/592"},{"key":"e_1_3_2_2_39_1","volume-title":"Deep graph contrastive representation learning. arXiv preprint arXiv:2006.04131","author":"Zhu Yanqiao","year":"2020","unstructured":"Yanqiao Zhu , Yichen Xu , Feng Yu , Qiang Liu , Shu Wu , and Liang Wang . 2020. Deep graph contrastive representation learning. arXiv preprint arXiv:2006.04131 ( 2020 ). Yanqiao Zhu, Yichen Xu, Feng Yu, Qiang Liu, Shu Wu, and Liang Wang. 2020. Deep graph contrastive representation learning. arXiv preprint arXiv:2006.04131 (2020)."},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3449802"}],"event":{"name":"CIKM '23: The 32nd ACM International Conference on Information and Knowledge Management","sponsor":["SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGIR ACM Special Interest Group on Information Retrieval"],"location":"Birmingham United Kingdom","acronym":"CIKM '23"},"container-title":["Proceedings of the 32nd ACM International Conference on Information and Knowledge Management"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3583780.3614917","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3583780.3614917","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:36:43Z","timestamp":1750178203000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3583780.3614917"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,10,21]]},"references-count":40,"alternative-id":["10.1145\/3583780.3614917","10.1145\/3583780"],"URL":"https:\/\/doi.org\/10.1145\/3583780.3614917","relation":{},"subject":[],"published":{"date-parts":[[2023,10,21]]},"assertion":[{"value":"2023-10-21","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}