{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T19:45:10Z","timestamp":1777059910243,"version":"3.51.4"},"publisher-location":"California","reference-count":0,"publisher":"International Joint Conferences on Artificial Intelligence Organization","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,8]]},"abstract":"<jats:p>Heterophily has been considered as an issue that hurts the performance of Graph Neural Networks (GNNs). To address this issue, some existing work uses a graph-level weighted fusion of the information of multi-hop neighbors to include more nodes with homophily. However, the heterophily might differ among nodes, which requires to consider the local topology. Motivated by it, we propose to use the local similarity (LocalSim) to learn node-level weighted fusion, which can also serve as a plug-and-play module. For better fusion, we propose a novel and efficient Initial Residual Difference Connection (IRDC) to extract more informative multi-hop information. Moreover, we provide theoretical analysis on the effectiveness of LocalSim representing node homophily on synthetic graphs. Extensive evaluations over real benchmark datasets show that our proposed method, namely Local Similarity Graph Neural Network (LSGNN), can offer comparable or superior state-of-the-art performance on both homophilic and heterophilic graphs. Meanwhile, the plug-and-play model can significantly boost the performance of existing GNNs.<\/jats:p>","DOI":"10.24963\/ijcai.2023\/395","type":"proceedings-article","created":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:31:30Z","timestamp":1691742690000},"page":"3550-3558","source":"Crossref","is-referenced-by-count":9,"title":["LSGNN: Towards General Graph Neural Network in Node Classification by Local Similarity"],"prefix":"10.24963","author":[{"given":"Yuhan","family":"Chen","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Guangzhou Campus of Sun Yat-sen University"}]},{"given":"Yihong","family":"Luo","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology (Guangzhou)"},{"name":"The Hong Kong University of Science and Technology"}]},{"given":"Jing","family":"Tang","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology (Guangzhou)"},{"name":"The Hong Kong University of Science and Technology"}]},{"given":"Liang","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Hebei University of Technology"}]},{"given":"Siya","family":"Qiu","sequence":"additional","affiliation":[{"name":"The Hong Kong University of Science and Technology (Guangzhou)"},{"name":"The Hong Kong University of Science and Technology"}]},{"given":"Chuan","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of Information Engineering, Chinese Academy of Sciences"}]},{"given":"Xiaochun","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University"}]}],"member":"10584","event":{"name":"Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}","theme":"Artificial Intelligence","location":"Macau, SAR China","acronym":"IJCAI-2023","number":"32","sponsor":["International Joint Conferences on Artificial Intelligence Organization (IJCAI)"],"start":{"date-parts":[[2023,8,19]]},"end":{"date-parts":[[2023,8,25]]}},"container-title":["Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2023,8,11]],"date-time":"2023-08-11T08:47:45Z","timestamp":1691743665000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.ijcai.org\/proceedings\/2023\/395"}},"subtitle":[],"proceedings-subject":"Artificial Intelligence Research Articles","short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":0,"URL":"https:\/\/doi.org\/10.24963\/ijcai.2023\/395","relation":{},"subject":[],"published":{"date-parts":[[2023,8]]}}}