{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T22:41:44Z","timestamp":1773528104311,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":59,"publisher":"ACM","license":[{"start":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T00:00:00Z","timestamp":1597881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"Huawei Noah's Ark Lab","award":["Gift Fund"],"award-info":[{"award-number":["Gift Fund"]}]},{"name":"Research Grants Council (RGC) in Hong Kong","award":["ECS No. 26206717"],"award-info":[{"award-number":["ECS No. 26206717"]}]},{"name":"Research Grants Council (RGC) in Hong Kong","award":["RIF No. R6020-19"],"award-info":[{"award-number":["RIF No. R6020-19"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,8,23]]},"DOI":"10.1145\/3394486.3403247","type":"proceedings-article","created":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T23:03:59Z","timestamp":1597964639000},"page":"1959-1969","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":59,"title":["Neural Subgraph Isomorphism Counting"],"prefix":"10.1145","author":[{"given":"Xin","family":"Liu","sequence":"first","affiliation":[{"name":"Hong Kong University of Science and Technology, Kowloon, Hong Kong"}]},{"given":"Haojie","family":"Pan","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology, Kowloon, Hong Kong"}]},{"given":"Mutian","family":"He","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology, Kowloon, Hong Kong"}]},{"given":"Yangqiu","family":"Song","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology, Kowloon, Hong Kong"}]},{"given":"Xin","family":"Jiang","sequence":"additional","affiliation":[{"name":"Huawei Technologies Co. Ltd, New Territories, Hong Kong"}]},{"given":"Lifeng","family":"Shang","sequence":"additional","affiliation":[{"name":"Huawei Technologies Co. Ltd, New Territories, Hong Kong"}]}],"member":"320","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"crossref","unstructured":"Noga Alon Phuong Dao Iman Hajirasouliha Fereydoun Hormozdiari and S\u00fcleyman Cenk Sahinalp. 2008. Biomolecular network motif counting and discovery by color coding. In ISMB. 241--249. Noga Alon Phuong Dao Iman Hajirasouliha Fereydoun Hormozdiari and S\u00fcleyman Cenk Sahinalp. 2008. Biomolecular network motif counting and discovery by color coding. In ISMB. 241--249.","DOI":"10.1093\/bioinformatics\/btn163"},{"key":"e_1_3_2_2_2_1","unstructured":"Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2015. Neural Machine Translation by Jointly Learning to Align and Translate. In ICLR. Dzmitry Bahdanau Kyunghyun Cho and Yoshua Bengio. 2015. Neural Machine Translation by Jointly Learning to Align and Translate. In ICLR."},{"key":"e_1_3_2_2_3_1","unstructured":"Peter W. Battaglia Jessica B. Hamrick Victor Bapst Alvaro Sanchez-Gonzalez Vin'i cius Flores Zambaldi Mateusz Malinowski Andrea Tacchetti David Raposo Adam Santoro Ryan Faulkner cC aglar G\u00fc lcc ehre H. Francis Song Andrew J. Ballard Justin Gilmer George E. Dahl Ashish Vaswani Kelsey R. Allen Charles Nash Victoria Langston Chris Dyer Nicolas Heess Daan Wierstra Pushmeet Kohli Matthew Botvinick Oriol Vinyals Yujia Li and Razvan Pascanu. 2018. Relational inductive biases deep learning and graph networks. CoRR Vol. abs\/1806.01261 (2018). Peter W. Battaglia Jessica B. Hamrick Victor Bapst Alvaro Sanchez-Gonzalez Vin'i cius Flores Zambaldi Mateusz Malinowski Andrea Tacchetti David Raposo Adam Santoro Ryan Faulkner cC aglar G\u00fc lcc ehre H. Francis Song Andrew J. Ballard Justin Gilmer George E. Dahl Ashish Vaswani Kelsey R. Allen Charles Nash Victoria Langston Chris Dyer Nicolas Heess Daan Wierstra Pushmeet Kohli Matthew Botvinick Oriol Vinyals Yujia Li and Razvan Pascanu. 2018. Relational inductive biases deep learning and graph networks. CoRR Vol. abs\/1806.01261 (2018)."},{"key":"e_1_3_2_2_4_1","volume-title":"Ronan Collobert, and Jason Weston.","author":"Bengio Yoshua","year":"2009","unstructured":"Yoshua Bengio , J\u00e9 r\u00f4 me Louradour , Ronan Collobert, and Jason Weston. 2009 . Curriculum learning. In ICML. 41--48. Yoshua Bengio, J\u00e9 r\u00f4 me Louradour, Ronan Collobert, and Jason Weston. 2009. Curriculum learning. In ICML. 41--48."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2017.2696940"},{"key":"e_1_3_2_2_6_1","unstructured":"Zhengdao Chen Soledad Villar Lei Chen and Joan Bruna. 2019. On the equivalence between graph isomorphism testing and function approximation with GNNs. In NeurIPS. 15868--15876. Zhengdao Chen Soledad Villar Lei Chen and Joan Bruna. 2019. On the equivalence between graph isomorphism testing and function approximation with GNNs. In NeurIPS. 15868--15876."},{"key":"e_1_3_2_2_7_1","volume-title":"Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio.","author":"Cho Kyunghyun","year":"2014","unstructured":"Kyunghyun Cho , Bart van Merrienboer , cC aglar G\u00fc lcc ehre , Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 . Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. In EMNLP. 1724--1734. Kyunghyun Cho, Bart van Merrienboer, cC aglar G\u00fc lcc ehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014. Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. In EMNLP. 1724--1734."},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2004.75"},{"key":"e_1_3_2_2_9_1","volume-title":"Quoc Viet Le, and Ruslan Salakhutdinov","author":"Dai Zihang","year":"2019","unstructured":"Zihang Dai , Zhilin Yang , Yiming Yang , Jaime G. Carbonell , Quoc Viet Le, and Ruslan Salakhutdinov . 2019 . Transformer-XL: Attentive Language Models beyond a Fixed-Length Context. In ACL. 2978--2988. Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc Viet Le, and Ruslan Salakhutdinov. 2019. Transformer-XL: Attentive Language Models beyond a Fixed-Length Context. In ACL. 2978--2988."},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1137\/15M1054389"},{"key":"e_1_3_2_2_11_1","unstructured":"Changjun Fan Li Zeng Yuhui Ding Muhao Chen Yizhou Sun and Zhong Liu. 2019. Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach. In CIKM. 559--568. Changjun Fan Li Zeng Yuhui Ding Muhao Chen Yizhou Sun and Zhong Liu. 2019. Learning to Identify High Betweenness Centrality Nodes from Scratch: A Novel Graph Neural Network Approach. In CIKM. 559--568."},{"key":"e_1_3_2_2_12_1","first-page":"264","article-title":"Graph Pattern Matching: From Intractable to Polynomial Time","volume":"3","author":"Fan Wenfei","year":"2010","unstructured":"Wenfei Fan , Jianzhong Li , Shuai Ma , Nan Tang , Yinghui Wu , and Yunpeng Wu . 2010 . Graph Pattern Matching: From Intractable to Polynomial Time . VLDB , Vol. 3 , 1 (2010), 264 -- 275 . Wenfei Fan, Jianzhong Li, Shuai Ma, Nan Tang, Yinghui Wu, and Yunpeng Wu. 2010. Graph Pattern Matching: From Intractable to Polynomial Time. VLDB, Vol. 3, 1 (2010), 264--275.","journal-title":"VLDB"},{"key":"e_1_3_2_2_13_1","volume-title":"Min Wu, Kevin Chen-Chuan Chang, and Xiaoli Li.","author":"Fang Yuan","year":"2016","unstructured":"Yuan Fang , Wenqing Lin , Vincent Wenchen Zheng , Min Wu, Kevin Chen-Chuan Chang, and Xiaoli Li. 2016 . Semantic proximity search on graphs with metagraph-based learning. In ICDE. 277--288. Yuan Fang, Wenqing Lin, Vincent Wenchen Zheng, Min Wu, Kevin Chen-Chuan Chang, and Xiaoli Li. 2016. Semantic proximity search on graphs with metagraph-based learning. In ICDE. 277--288."},{"key":"e_1_3_2_2_14_1","first-page":"729","article-title":"A new model for learning in graph domains","volume":"2","author":"Gori Michele","year":"2005","unstructured":"Michele Gori , Gabriele Monfardini , and Franco Scarselli . 2005 . A new model for learning in graph domains . IJCNN , Vol. 2 (2005), 729 -- 734 . Michele Gori, Gabriele Monfardini, and Franco Scarselli. 2005. A new model for learning in graph domains. IJCNN, Vol. 2 (2005), 729--734.","journal-title":"IJCNN"},{"key":"e_1_3_2_2_15_1","volume-title":"Nature","volume":"538","author":"Graves Alex","year":"2016","unstructured":"Alex Graves , Greg Wayne , Malcolm Reynolds , Tim Harley , Ivo Danihelka , Agnieszka Grabska-Barwinska , Sergio Gomez Colmenarejo , Edward Grefenstette , Tiago Ramalho , John Agapiou , Adri\u00e0 Puigdom\u00e8 nech Badia , Karl Moritz Hermann , Yori Zwols , Georg Ostrovski , Adam Cain , Helen King , Christopher Summerfield , Phil Blunsom , Koray Kavukcuoglu , and Demis Hassabis . 2016 . Hybrid computing using a neural network with dynamic external memory . Nature , Vol. 538 , 7626 (2016), 471--476. Alex Graves, Greg Wayne, Malcolm Reynolds, Tim Harley, Ivo Danihelka, Agnieszka Grabska-Barwinska, Sergio Gomez Colmenarejo, Edward Grefenstette, Tiago Ramalho, John Agapiou, Adri\u00e0 Puigdom\u00e8 nech Badia, Karl Moritz Hermann, Yori Zwols, Georg Ostrovski, Adam Cain, Helen King, Christopher Summerfield, Phil Blunsom, Koray Kavukcuoglu, and Demis Hassabis. 2016. Hybrid computing using a neural network with dynamic external memory. Nature, Vol. 538, 7626 (2016), 471--476."},{"key":"e_1_3_2_2_16_1","doi-asserted-by":"crossref","unstructured":"Aditya Grover and Jure Leskovec. 2016. node2vec: Scalable Feature Learning for Networks. In SIGKDD. 855--864. Aditya Grover and Jure Leskovec. 2016. node2vec: Scalable Feature Learning for Networks. In SIGKDD. 855--864.","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_2_17_1","first-page":"52","article-title":"Representation Learning on Graphs","volume":"40","author":"Hamilton William L.","year":"2017","unstructured":"William L. Hamilton , Rex Ying , and Jure Leskovec . 2017 a. Representation Learning on Graphs : Methods and Applications. IEEE Data Eng. Bull. , Vol. 40 , 3 (2017), 52 -- 74 . William L. Hamilton, Rex Ying, and Jure Leskovec. 2017a. Representation Learning on Graphs: Methods and Applications. IEEE Data Eng. Bull., Vol. 40, 3 (2017), 52--74.","journal-title":"Methods and Applications. IEEE Data Eng. Bull."},{"key":"e_1_3_2_2_18_1","unstructured":"William L. Hamilton Zhitao Ying and Jure Leskovec. 2017b. Inductive Representation Learning on Large Graphs. In NeurIPS. 1024--1034. William L. Hamilton Zhitao Ying and Jure Leskovec. 2017b. Inductive Representation Learning on Large Graphs. In NeurIPS. 1024--1034."},{"key":"e_1_3_2_2_19_1","unstructured":"Wook-Shin Han Jinsoo Lee and Jeong-Hoon Lee. 2013. Turbo(_iso ): towards ultrafast and robust subgraph isomorphism search in large graph databases. In SIGMOD. 337--348. Wook-Shin Han Jinsoo Lee and Jeong-Hoon Lee. 2013. Turbo(_iso ): towards ultrafast and robust subgraph isomorphism search in large graph databases. In SIGMOD. 337--348."},{"key":"e_1_3_2_2_20_1","volume-title":"Singh","author":"He Huahai","year":"2008","unstructured":"Huahai He and Ambuj K . Singh . 2008 . Graphs-at-a-time: query language and access methods for graph databases. In SIGMOD. 405--418. Huahai He and Ambuj K. Singh. 2008. Graphs-at-a-time: query language and access methods for graph databases. In SIGMOD. 405--418."},{"key":"e_1_3_2_2_21_1","unstructured":"Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In CVPR. 770--778. Kaiming He Xiangyu Zhang Shaoqing Ren and Jian Sun. 2016. Deep Residual Learning for Image Recognition. In CVPR. 770--778."},{"key":"e_1_3_2_2_22_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"crossref","unstructured":"Minghao Hu Yuxing Peng Zhen Huang Xipeng Qiu Furu Wei and Ming Zhou. 2018. Reinforced Mnemonic Reader for Machine Reading Comprehension. In IJCAI. 4099--4106. Minghao Hu Yuxing Peng Zhen Huang Xipeng Qiu Furu Wei and Ming Zhou. 2018. Reinforced Mnemonic Reader for Machine Reading Comprehension. In IJCAI. 4099--4106.","DOI":"10.24963\/ijcai.2018\/570"},{"key":"e_1_3_2_2_24_1","volume-title":"Prins","author":"Huan Jun","year":"2003","unstructured":"Jun Huan , Wei Wang , and Jan F . Prins . 2003 . Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism. In ICDM. 549--552. Jun Huan, Wei Wang, and Jan F. Prins. 2003. Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism. In ICDM. 549--552."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939815"},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"crossref","unstructured":"He Jiang Yangqiu Song Chenguang Wang Ming Zhang and Yizhou Sun. 2017. Semi-supervised Learning over Heterogeneous Information Networks by Ensemble of Meta-graph Guided Random Walks. In IJCAI. 1944--1950. He Jiang Yangqiu Song Chenguang Wang Ming Zhang and Yizhou Sun. 2017. Semi-supervised Learning over Heterogeneous Information Networks by Ensemble of Meta-graph Guided Random Walks. In IJCAI. 1944--1950.","DOI":"10.24963\/ijcai.2017\/270"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"crossref","unstructured":"Yoon Kim. 2014. Convolutional Neural Networks for Sentence Classification. In EMNLP. 1746--1751. Yoon Kim. 2014. Convolutional Neural Networks for Sentence Classification. In EMNLP. 1746--1751.","DOI":"10.3115\/v1\/D14-1181"},{"key":"e_1_3_2_2_28_1","volume-title":"Kipf and Max Welling","author":"Thomas","year":"2017","unstructured":"Thomas N. Kipf and Max Welling . 2017 . Semi-Supervised Classification with Graph Convolutional Networks. In ICLR. Thomas N. Kipf and Max Welling. 2017. Semi-Supervised Classification with Graph Convolutional Networks. In ICLR."},{"key":"e_1_3_2_2_29_1","unstructured":"Ankit Kumar Ozan Irsoy Peter Ondruska Mohit Iyyer James Bradbury Ishaan Gulrajani Victor Zhong Romain Paulus and Richard Socher. 2016. Ask Me Anything: Dynamic Memory Networks for Natural Language Processing. In ICML. 1378--1387. Ankit Kumar Ozan Irsoy Peter Ondruska Mohit Iyyer James Bradbury Ishaan Gulrajani Victor Zhong Romain Paulus and Richard Socher. 2016. Ask Me Anything: Dynamic Memory Networks for Natural Language Processing. In ICML. 1378--1387."},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"crossref","unstructured":"Michihiro Kuramochi and George Karypis. 2004. GREW-A Scalable Frequent Subgraph Discovery Algorithm. In ICDM. 439--442. Michihiro Kuramochi and George Karypis. 2004. GREW-A Scalable Frequent Subgraph Discovery Algorithm. In ICDM. 439--442.","DOI":"10.21236\/ADA439436"},{"key":"e_1_3_2_2_31_1","volume-title":"Zemel","author":"Li Yujia","year":"2016","unstructured":"Yujia Li , Daniel Tarlow , Marc Brockschmidt , and Richard S . Zemel . 2016 . Gated Graph Sequence Neural Networks. In ICLR. Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard S. Zemel. 2016. Gated Graph Sequence Neural Networks. In ICLR."},{"key":"e_1_3_2_2_32_1","unstructured":"Ilya Loshchilov and Frank Hutter. 2019. Decoupled Weight Decay Regularization. In ICLR. Ilya Loshchilov and Frank Hutter. 2019. Decoupled Weight Decay Regularization. In ICLR."},{"key":"e_1_3_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1145\/2528937"},{"key":"e_1_3_2_2_34_1","volume-title":"Science","volume":"298","author":"Milo Ron","year":"2002","unstructured":"Ron Milo , Shai Shen-Orr , Shalev Itzkovitz , Nadav Kashtan , Dmitri Chklovskii , and Uri Alon . 2002 . Network motifs: simple building blocks of complex networks . Science , Vol. 298 , 5594 (2002), 824--827. Ron Milo, Shai Shen-Orr, Shalev Itzkovitz, Nadav Kashtan, Dmitri Chklovskii, and Uri Alon. 2002. Network motifs: simple building blocks of complex networks. Science, Vol. 298, 5594 (2002), 824--827."},{"key":"e_1_3_2_2_35_1","unstructured":"Mathias Niepert Mohamed Ahmed and Konstantin Kutzkov. 2016. Learning Convolutional Neural Networks for Graphs. In ICML. 2014--2023. Mathias Niepert Mohamed Ahmed and Konstantin Kutzkov. 2016. Learning Convolutional Neural Networks for Graphs. In ICML. 2014--2023."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.191"},{"key":"e_1_3_2_2_37_1","doi-asserted-by":"crossref","unstructured":"Bryan Perozzi Rami Al-Rfou and Steven Skiena. 2014. DeepWalk: online learning of social representations. In SIGKDD. 701--710. Bryan Perozzi Rami Al-Rfou and Steven Skiena. 2014. DeepWalk: online learning of social representations. In SIGKDD. 701--710.","DOI":"10.1145\/2623330.2623732"},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btl030"},{"key":"e_1_3_2_2_39_1","volume-title":"Marco Gori, Markus Hagenbuchner, Ah Chung Tsoi, and Marco Maggini.","author":"Scarselli Franco","year":"2005","unstructured":"Franco Scarselli , Sweah Liang Yong , Marco Gori, Markus Hagenbuchner, Ah Chung Tsoi, and Marco Maggini. 2005 . Graph Neural Networks for Ranking Web Pages. In WI. 666--672. Franco Scarselli, Sweah Liang Yong, Marco Gori, Markus Hagenbuchner, Ah Chung Tsoi, and Marco Maggini. 2005. Graph Neural Networks for Ranking Web Pages. In WI. 666--672."},{"key":"e_1_3_2_2_40_1","doi-asserted-by":"crossref","unstructured":"Michael Sejr Schlichtkrull Thomas N. Kipf Peter Bloem Rianne van den Berg Ivan Titov and Max Welling. 2018. Modeling Relational Data with Graph Convolutional Networks. In ESWC. 593--607. Michael Sejr Schlichtkrull Thomas N. Kipf Peter Bloem Rianne van den Berg Ivan Titov and Max Welling. 2018. Modeling Relational Data with Graph Convolutional Networks. In ESWC. 593--607.","DOI":"10.1007\/978-3-319-93417-4_38"},{"key":"e_1_3_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.5555\/1953048.2078187"},{"key":"e_1_3_2_2_42_1","unstructured":"Sainbayar Sukhbaatar Arthur Szlam Jason Weston and Rob Fergus. 2015. End-To-End Memory Networks. In NeurIPS. 2440--2448. Sainbayar Sukhbaatar Arthur Szlam Jason Weston and Rob Fergus. 2015. End-To-End Memory Networks. In NeurIPS. 2440--2448."},{"key":"e_1_3_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.14778\/2311906.2311907"},{"key":"e_1_3_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741093"},{"key":"e_1_3_2_2_45_1","doi-asserted-by":"crossref","unstructured":"Carlos H. C. Teixeira Leornado Cotta Bruno Ribeiro and Wagner Meira Jr. 2018. Graph Pattern Mining and Learning through User-Defined Relations. In ICDM. 1266--1271. Carlos H. C. Teixeira Leornado Cotta Bruno Ribeiro and Wagner Meira Jr. 2018. Graph Pattern Mining and Learning through User-Defined Relations. In ICDM. 1266--1271.","DOI":"10.1109\/ICDM.2018.00170"},{"key":"e_1_3_2_2_46_1","volume-title":"Bastian Rieck, and Karsten M. Borgwardt.","author":"Togninalli Matteo","year":"2019","unstructured":"Matteo Togninalli , M. Elisabetta Ghisu , Felipe Llinares-L\u00f3 pez , Bastian Rieck, and Karsten M. Borgwardt. 2019 . Wasserstein Weisfeiler-Lehman Graph Kernels. In NeurIPS. 6436--6446. Matteo Togninalli, M. Elisabetta Ghisu, Felipe Llinares-L\u00f3 pez, Bastian Rieck, and Karsten M. Borgwardt. 2019. Wasserstein Weisfeiler-Lehman Graph Kernels. In NeurIPS. 6436--6446."},{"key":"e_1_3_2_2_47_1","doi-asserted-by":"crossref","unstructured":"Charalampos E. Tsourakakis. 2008. Fast Counting of Triangles in Large Real Networks without Counting: Algorithms and Laws. In ICDM. 608--617. Charalampos E. Tsourakakis. 2008. Fast Counting of Triangles in Large Real Networks without Counting: Algorithms and Laws. In ICDM. 608--617.","DOI":"10.1109\/ICDM.2008.72"},{"key":"e_1_3_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1145\/321921.321925"},{"key":"e_1_3_2_2_49_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is All you Need. In NeurIPS. 5998--6008. Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N Gomez \u0141ukasz Kaiser and Illia Polosukhin. 2017. Attention is All you Need. In NeurIPS. 5998--6008."},{"key":"e_1_3_2_2_50_1","unstructured":"Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Li\u00f2 and Yoshua Bengio. 2018. Graph Attention Networks. In ICLR. Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Li\u00f2 and Yoshua Bengio. 2018. Graph Attention Networks. In ICLR."},{"key":"e_1_3_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.5555\/1756006.1859891"},{"key":"e_1_3_2_2_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/2629564"},{"key":"e_1_3_2_2_53_1","unstructured":"Keyulu Xu Weihua Hu Jure Leskovec and Stefanie Jegelka. 2019. How Powerful are Graph Neural Networks?. In ICLR. Keyulu Xu Weihua Hu Jure Leskovec and Stefanie Jegelka. 2019. How Powerful are Graph Neural Networks?. In ICLR."},{"key":"e_1_3_2_2_54_1","unstructured":"Keyulu Xu Jingling Li Mozhi Zhang Simon S. Du Ken-ichi Kawarabayashi and Stefanie Jegelka. 2020. What Can Neural Networks Reason About?. In ICLR. Keyulu Xu Jingling Li Mozhi Zhang Simon S. Du Ken-ichi Kawarabayashi and Stefanie Jegelka. 2020. What Can Neural Networks Reason About?. In ICLR."},{"key":"e_1_3_2_2_55_1","unstructured":"Xifeng Yan and Jiawei Han. 2002. gSpan: Graph-Based Substructure Pattern Mining. In ICDM. 721--724. Xifeng Yan and Jiawei Han. 2002. gSpan: Graph-Based Substructure Pattern Mining. In ICDM. 721--724."},{"key":"e_1_3_2_2_56_1","doi-asserted-by":"publisher","DOI":"10.1145\/1007568.1007607"},{"key":"e_1_3_2_2_57_1","doi-asserted-by":"crossref","unstructured":"Pinar Yanardag and S. V. N. Vishwanathan. 2015. Deep Graph Kernels. In SIGKDD. 1365--1374. Pinar Yanardag and S. V. N. Vishwanathan. 2015. Deep Graph Kernels. In SIGKDD. 1365--1374.","DOI":"10.1145\/2783258.2783417"},{"key":"e_1_3_2_2_58_1","unstructured":"Jiaxuan You Rex Ying Xiang Ren William L. Hamilton and Jure Leskovec. 2018. GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models. In ICML. 5694--5703. Jiaxuan You Rex Ying Xiang Ren William L. Hamilton and Jure Leskovec. 2018. GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models. In ICML. 5694--5703."},{"key":"e_1_3_2_2_59_1","doi-asserted-by":"crossref","unstructured":"Huan Zhao Quanming Yao Jianda Li Yangqiu Song and Dik Lun Lee. 2017. Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks. In SIGKDD. 635--644. Huan Zhao Quanming Yao Jianda Li Yangqiu Song and Dik Lun Lee. 2017. Meta-Graph Based Recommendation Fusion over Heterogeneous Information Networks. In SIGKDD. 635--644.","DOI":"10.1145\/3097983.3098063"}],"event":{"name":"KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Virtual Event CA USA","acronym":"KDD '20","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"]},"container-title":["Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery &amp; Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394486.3403247","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3394486.3403247","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T22:01:47Z","timestamp":1750197707000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3394486.3403247"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,8,20]]},"references-count":59,"alternative-id":["10.1145\/3394486.3403247","10.1145\/3394486"],"URL":"https:\/\/doi.org\/10.1145\/3394486.3403247","relation":{},"subject":[],"published":{"date-parts":[[2020,8,20]]},"assertion":[{"value":"2020-08-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}