{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T11:57:13Z","timestamp":1679486233571},"publisher-location":"New York, NY, USA","reference-count":42,"publisher":"ACM","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2020,1,20]]},"DOI":"10.1145\/3336191.3371845","type":"proceedings-article","created":{"date-parts":[[2020,1,22]],"date-time":"2020-01-22T19:08:16Z","timestamp":1579720096000},"update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":123,"title":["DySAT"],"prefix":"10.1145","author":[{"given":"Aravind","family":"Sankar","sequence":"first","affiliation":[{"name":"University of Illinois, Urbana-Champaign, Champaign, IL, USA"}]},{"given":"Yanhong","family":"Wu","sequence":"additional","affiliation":[{"name":"Visa Research, Palo Alto, CA, USA"}]},{"given":"Liang","family":"Gou","sequence":"additional","affiliation":[{"name":"Visa Research, Palo Alto, CA, USA"}]},{"given":"Wei","family":"Zhang","sequence":"additional","affiliation":[{"name":"Visa Research, Palo Alto, CA, USA"}]},{"given":"Hao","family":"Yang","sequence":"additional","affiliation":[{"name":"Visa Research, Palo Alto, CA, USA"}]}],"member":"320","published-online":{"date-parts":[[2020,1,22]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"et almbox","author":"Abadi Mart'in","year":"2016","unstructured":"Mart'in Abadi , Ashish Agarwal , Paul Barham , Eugene Brevdo , Zhifeng Chen , Craig Citro , Greg S Corrado , Andy Davis , Jeffrey Dean , Matthieu Devin , et almbox . 2016 . Tensorflow : Large-scale machine learning on heterogeneous distributed systems. arXiv preprint arXiv:1603.04467 (2016). Mart'in Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, et almbox. 2016. Tensorflow: Large-scale machine learning on heterogeneous distributed systems. arXiv preprint arXiv:1603.04467 (2016)."},{"key":"e_1_3_2_1_2_1","volume-title":"International Conference on Learning Representations (ICLR) .","author":"Bahdanau Dzmitry","year":"2015","unstructured":"Dzmitry Bahdanau , Kyunghyun Cho , and Yoshua Bengio . 2015 . Neural Machine Translation by Jointly Learning to Align and Translate . In International Conference on Learning Representations (ICLR) . Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015. Neural Machine Translation by Jointly Learning to Align and Translate. In International Conference on Learning Representations (ICLR) ."},{"key":"e_1_3_2_1_3_1","unstructured":"Micha\u00ebl Defferrard Xavier Bresson and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. In Advances in neural information processing systems. 3844--3852. Micha\u00ebl Defferrard Xavier Bresson and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. In Advances in neural information processing systems. 3844--3852."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Lun Du Yun Wang Guojie Song Zhicong Lu and Junshan Wang. 2018. Dynamic Network Embedding: An Extended Approach for Skip-gram based Network Embedding.. In IJCAI . 2086--2092. Lun Du Yun Wang Guojie Song Zhicong Lu and Junshan Wang. 2018. Dynamic Network Embedding: An Extended Approach for Skip-gram based Network Embedding.. In IJCAI . 2086--2092.","DOI":"10.24963\/ijcai.2018\/288"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.5555\/3305381.3305510"},{"key":"e_1_3_2_1_6_1","volume-title":"Sujit Rokka Chhetri, and Arquimedes Canedo","author":"Goyal Palash","year":"2018","unstructured":"Palash Goyal , Sujit Rokka Chhetri, and Arquimedes Canedo . 2018 . dyngraph2vec: Capturing network dynamics using dynamic graph representation learning. arXiv preprint arXiv:1809.02657 (2018). Palash Goyal, Sujit Rokka Chhetri, and Arquimedes Canedo. 2018. dyngraph2vec: Capturing network dynamics using dynamic graph representation learning. arXiv preprint arXiv:1809.02657 (2018)."},{"key":"e_1_3_2_1_7_1","volume-title":"DynGEM: Deep Embedding Method for Dynamic Graphs. In IJCAI International Workshop on Representation Learning for Graphs (ReLiG) .","author":"Goyal Palash","year":"2017","unstructured":"Palash Goyal , Nitin Kamra , Xinran He , and Yan Liu . 2017 . DynGEM: Deep Embedding Method for Dynamic Graphs. In IJCAI International Workshop on Representation Learning for Graphs (ReLiG) . Palash Goyal, Nitin Kamra, Xinran He, and Yan Liu. 2017. DynGEM: Deep Embedding Method for Dynamic Graphs. In IJCAI International Workshop on Representation Learning for Graphs (ReLiG) ."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_1_9_1","unstructured":"Ehsan Hajiramezanali Arman Hasanzadeh Krishna Narayanan Nick Duffield Mingyuan Zhou and Xiaoning Qian. 2019. Variational graph recurrent neural networks. In Advances in Neural Information Processing Systems. 10700--10710. Ehsan Hajiramezanali Arman Hasanzadeh Krishna Narayanan Nick Duffield Mingyuan Zhou and Xiaoning Qian. 2019. Variational graph recurrent neural networks. In Advances in Neural Information Processing Systems. 10700--10710."},{"key":"e_1_3_2_1_10_1","unstructured":"Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In Advances in Neural Information Processing Systems. 1024--1034. Will Hamilton Zhitao Ying and Jure Leskovec. 2017. Inductive representation learning on large graphs. In Advances in Neural Information Processing Systems. 1024--1034."},{"key":"e_1_3_2_1_11_1","first-page":"19","article-title":"The movielens datasets: History and context","volume":"5","author":"Maxwell Harper F","year":"2016","unstructured":"F Maxwell Harper and Joseph A Konstan . 2016 . The movielens datasets: History and context . ACM Transactions on Interactive Intelligent Systems (TIIS) , Vol. 5 , 4 (2016), 19 . F Maxwell Harper and Joseph A Konstan. 2016. The movielens datasets: History and context. ACM Transactions on Interactive Intelligent Systems (TIIS) , Vol. 5, 4 (2016), 19.","journal-title":"ACM Transactions on Interactive Intelligent Systems (TIIS)"},{"key":"e_1_3_2_1_12_1","volume-title":"International Conference on Learning Representations (ICLR) .","author":"Kingma Diederik P","year":"2015","unstructured":"Diederik P Kingma and Jimmy Ba . 2015 . Adam: A method for stochastic optimization . In International Conference on Learning Representations (ICLR) . Diederik P Kingma and Jimmy Ba. 2015. Adam: A method for stochastic optimization. In International Conference on Learning Representations (ICLR) ."},{"key":"e_1_3_2_1_13_1","volume-title":"International Conference for Learning Representations (ICLR) .","author":"Kipf Thomas N","year":"2017","unstructured":"Thomas N Kipf and Max Welling . 2017 . Semi-supervised classification with graph convolutional networks . In International Conference for Learning Representations (ICLR) . Thomas N Kipf and Max Welling. 2017. Semi-supervised classification with graph convolutional networks. In International Conference for Learning Representations (ICLR) ."},{"key":"e_1_3_2_1_14_1","volume-title":"Introducing the Enron Corpus. In CEAS 2004 - First Conference on Email and Anti-Spam, July 30--31","author":"Klimt Bryan","year":"2004","unstructured":"Bryan Klimt and Yiming Yang . 2004 . Introducing the Enron Corpus. In CEAS 2004 - First Conference on Email and Anti-Spam, July 30--31 , 2004, Mountain View, California, USA. Bryan Klimt and Yiming Yang. 2004. Introducing the Enron Corpus. In CEAS 2004 - First Conference on Email and Anti-Spam, July 30--31, 2004, Mountain View, California, USA."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357898"},{"key":"e_1_3_2_1_16_1","volume-title":"Graph evolution: Densification and shrinking diameters. ACM Transactions on Knowledge Discovery from Data (TKDD)","author":"Leskovec Jure","year":"2007","unstructured":"Jure Leskovec , Jon Kleinberg , and Christos Faloutsos . 2007. Graph evolution: Densification and shrinking diameters. ACM Transactions on Knowledge Discovery from Data (TKDD) , Vol. 1 , 1 ( 2007 ), 2. Jure Leskovec, Jon Kleinberg, and Christos Faloutsos. 2007. Graph evolution: Densification and shrinking diameters. ACM Transactions on Knowledge Discovery from Data (TKDD) , Vol. 1, 1 (2007), 2."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/3132847.3132919"},{"key":"e_1_3_2_1_18_1","volume-title":"Streaming Network Embedding through Local Actions. arXiv preprint arXiv:1811.05932","author":"Liu Xi","year":"2018","unstructured":"Xi Liu , Ping-Chun Hsieh , Nick Duffield , Rui Chen , Muhe Xie , and Xidao Wen . 2018. Streaming Network Embedding through Local Actions. arXiv preprint arXiv:1811.05932 ( 2018 ). Xi Liu, Ping-Chun Hsieh, Nick Duffield, Rui Chen, Muhe Xie, and Xidao Wen. 2018. Streaming Network Embedding through Local Actions. arXiv preprint arXiv:1811.05932 (2018)."},{"key":"e_1_3_2_1_19_1","volume-title":"An Induced Multi-Relational Framework for Answer Selection in Community Question Answer Platforms. arXiv preprint arXiv:1911.06957","author":"Narang Kanika","year":"2019","unstructured":"Kanika Narang , Chaoqi Yang , Adit Krishnan , Junting Wang , Hari Sundaram , and Carolyn Sutter . 2019. An Induced Multi-Relational Framework for Answer Selection in Community Question Answer Platforms. arXiv preprint arXiv:1911.06957 ( 2019 ). Kanika Narang, Chaoqi Yang, Adit Krishnan, Junting Wang, Hari Sundaram, and Carolyn Sutter. 2019. An Induced Multi-Relational Framework for Answer Selection in Community Question Answer Platforms. arXiv preprint arXiv:1911.06957 (2019)."},{"key":"e_1_3_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/3184558.3191526"},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1002\/asi.21015"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623732"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN.2019.8852147"},{"key":"e_1_3_2_1_24_1","volume-title":"Dynamic Graph Representation Learning via Self-Attention Networks. arXiv preprint arXiv:1812.09430","author":"Sankar Aravind","year":"2018","unstructured":"Aravind Sankar , Yanhong Wu , Liang Gou , Wei Zhang , and Hao Yang . 2018. Dynamic Graph Representation Learning via Self-Attention Networks. arXiv preprint arXiv:1812.09430 ( 2018 ). Aravind Sankar, Yanhong Wu, Liang Gou, Wei Zhang, and Hao Yang. 2018. Dynamic Graph Representation Learning via Self-Attention Networks. arXiv preprint arXiv:1812.09430 (2018)."},{"key":"e_1_3_2_1_25_1","volume-title":"Motif-based Convolutional Neural Network on Graphs. CoRR","author":"Sankar Aravind","year":"2017","unstructured":"Aravind Sankar , Xinyang Zhang , and Kevin Chen-Chuan Chang . 2017. Motif-based Convolutional Neural Network on Graphs. CoRR , Vol. abs\/ 1711 .05697 ( 2017 ). arxiv: 1711.05697 Aravind Sankar, Xinyang Zhang, and Kevin Chen-Chuan Chang. 2017. Motif-based Convolutional Neural Network on Graphs. CoRR , Vol. abs\/1711.05697 (2017). arxiv: 1711.05697"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3341161.3342859"},{"key":"e_1_3_2_1_27_1","unstructured":"Purnamrita Sarkar and Andrew W Moore. 2006. Dynamic social network analysis using latent space models. In Advances in Neural Information Processing Systems. 1145--1152. Purnamrita Sarkar and Andrew W Moore. 2006. Dynamic social network analysis using latent space models. In Advances in Neural Information Processing Systems. 1145--1152."},{"key":"e_1_3_2_1_28_1","volume-title":"Thirty-Second AAAI Conference on Artificial Intelligence .","author":"Shen Tao","year":"2018","unstructured":"Tao Shen , Tianyi Zhou , Guodong Long , Jing Jiang , Shirui Pan , and Chengqi Zhang . 2018 . Disan: Directional self-attention network for rnn\/cnn-free language understanding . In Thirty-Second AAAI Conference on Artificial Intelligence . Tao Shen, Tianyi Zhou, Guodong Long, Jing Jiang, Shirui Pan, and Chengqi Zhang. 2018. Disan: Directional self-attention network for rnn\/cnn-free language understanding. In Thirty-Second AAAI Conference on Artificial Intelligence ."},{"key":"e_1_3_2_1_29_1","volume-title":"Thirty-Second AAAI Conference on Artificial Intelligence .","author":"Tan Zhixing","year":"2018","unstructured":"Zhixing Tan , Mingxuan Wang , Jun Xie , Yidong Chen , and Xiaodong Shi . 2018 . Deep semantic role labeling with self-attention . In Thirty-Second AAAI Conference on Artificial Intelligence . Zhixing Tan, Mingxuan Wang, Jun Xie, Yidong Chen, and Xiaodong Shi. 2018. Deep semantic role labeling with self-attention. In Thirty-Second AAAI Conference on Artificial Intelligence ."},{"key":"e_1_3_2_1_30_1","volume-title":"Vin De Silva, and John C Langford","author":"Tenenbaum Joshua B","year":"2000","unstructured":"Joshua B Tenenbaum , Vin De Silva, and John C Langford . 2000 . A global geometric framework for nonlinear dimensionality reduction. science , Vol. 290 , 5500 (2000), 2319--2323. Joshua B Tenenbaum, Vin De Silva, and John C Langford. 2000. A global geometric framework for nonlinear dimensionality reduction. science , Vol. 290, 5500 (2000), 2319--2323."},{"key":"e_1_3_2_1_31_1","volume-title":"Proceedings of the 34th International Conference on Machine Learning-Volume 70","author":"Trivedi Rakshit","year":"2017","unstructured":"Rakshit Trivedi , Hanjun Dai , Yichen Wang , and Le Song . 2017 . Know-evolve: Deep temporal reasoning for dynamic knowledge graphs . In Proceedings of the 34th International Conference on Machine Learning-Volume 70 . JMLR. org, 3462--3471. Rakshit Trivedi, Hanjun Dai, Yichen Wang, and Le Song. 2017. Know-evolve: Deep temporal reasoning for dynamic knowledge graphs. In Proceedings of the 34th International Conference on Machine Learning-Volume 70. JMLR. org, 3462--3471."},{"key":"e_1_3_2_1_32_1","volume-title":"Representation Learning over Dynamic Graphs. arXiv preprint arXiv:1803.04051","author":"Trivedi Rakshit","year":"2018","unstructured":"Rakshit Trivedi , Mehrdad Farajtbar , Prasenjeet Biswal , and Hongyuan Zha . 2018. Representation Learning over Dynamic Graphs. arXiv preprint arXiv:1803.04051 ( 2018 ). Rakshit Trivedi, Mehrdad Farajtbar, Prasenjeet Biswal, and Hongyuan Zha. 2018. Representation Learning over Dynamic Graphs. arXiv preprint arXiv:1803.04051 (2018)."},{"key":"e_1_3_2_1_33_1","unstructured":"Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Lukasz Kaiser and Illia Polosukhin. 2017. Attention is All you Need. In Advances in Neural Information Processing Systems. 6000--6010. Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Lukasz Kaiser and Illia Polosukhin. 2017. Attention is All you Need. In Advances in Neural Information Processing Systems. 6000--6010."},{"key":"e_1_3_2_1_34_1","volume-title":"International Conference on Learning Representations (ICLR) .","author":"Velickovic Petar","year":"2018","unstructured":"Petar Velickovic , Guillem Cucurull , Arantxa Casanova , Adriana Romero , Pietro Lio , and Yoshua Bengio . 2018 . Graph attention networks . In International Conference on Learning Representations (ICLR) . Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Lio, and Yoshua Bengio. 2018. Graph attention networks. In International Conference on Learning Representations (ICLR) ."},{"key":"e_1_3_2_1_35_1","volume-title":"Deep graph infomax. arXiv preprint arXiv:1809.10341","author":"Petar Velivc","year":"2018","unstructured":"Petar Velivc kovi\u0107 , William Fedus , William L Hamilton , Pietro Li\u00f2 , Yoshua Bengio , and R Devon Hjelm . 2018. Deep graph infomax. arXiv preprint arXiv:1809.10341 ( 2018 ). Petar Velivc kovi\u0107 , William Fedus, William L Hamilton, Pietro Li\u00f2, Yoshua Bengio, and R Devon Hjelm. 2018. Deep graph infomax. arXiv preprint arXiv:1809.10341 (2018)."},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.5555\/2893873.2894046"},{"key":"e_1_3_2_1_37_1","volume-title":"QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension. In International Conference on Learning Representations (ICLR) .","author":"Yu Adams Wei","unstructured":"Adams Wei Yu , David Dohan , Minh-Thang Luong , Rui Zhao , Kai Chen , Mohammad Norouzi , and Quoc V. Le . 2018 . QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension. In International Conference on Learning Representations (ICLR) . Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, and Quoc V. Le. 2018. QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension. In International Conference on Learning Representations (ICLR) ."},{"key":"e_1_3_2_1_38_1","volume-title":"Thirty-Second AAAI Conference on Artificial Intelligence .","author":"Zhang Ziwei","year":"2018","unstructured":"Ziwei Zhang , Peng Cui , Jian Pei , Xiao Wang , and Wenwu Zhu . 2018 . Timers: Error-bounded svd restart on dynamic networks . In Thirty-Second AAAI Conference on Artificial Intelligence . Ziwei Zhang, Peng Cui, Jian Pei, Xiao Wang, and Wenwu Zhu. 2018. Timers: Error-bounded svd restart on dynamic networks. In Thirty-Second AAAI Conference on Artificial Intelligence ."},{"key":"e_1_3_2_1_39_1","volume-title":"Thirty-Second AAAI Conference on Artificial Intelligence .","author":"Zhou Lekui","year":"2018","unstructured":"Lekui Zhou , Yang Yang , Xiang Ren , Fei Wu , and Yueting Zhuang . 2018 . Dynamic network embedding by modeling triadic closure process . In Thirty-Second AAAI Conference on Artificial Intelligence . Lekui Zhou, Yang Yang, Xiang Ren, Fei Wu, and Yueting Zhuang. 2018. Dynamic network embedding by modeling triadic closure process. In Thirty-Second AAAI Conference on Artificial Intelligence ."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2016.2591009"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bty294"},{"key":"e_1_3_2_1_42_1","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220054"}],"event":{"name":"WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining","location":"Houston TX USA","acronym":"WSDM '20","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGWEB ACM Special Interest Group on Hypertext, Hypermedia, and Web","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data","SIGIR ACM Special Interest Group on Information Retrieval"]},"container-title":["Proceedings of the 13th International Conference on Web Search and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3336191.3371845","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T14:02:21Z","timestamp":1673532141000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3336191.3371845"}},"subtitle":["Deep Neural Representation Learning on Dynamic Graphs via Self-Attention Networks"],"short-title":[],"issued":{"date-parts":[[2020,1,20]]},"references-count":42,"alternative-id":["10.1145\/3336191.3371845","10.1145\/3336191"],"URL":"http:\/\/dx.doi.org\/10.1145\/3336191.3371845","relation":{},"published":{"date-parts":[[2020,1,20]]},"assertion":[{"value":"2020-01-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}