{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T15:02:21Z","timestamp":1776092541911,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":38,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,8,14]],"date-time":"2021-08-14T00:00:00Z","timestamp":1628899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U2001212, 62032001, 61932004, 62002343"],"award-info":[{"award-number":["U2001212, 62032001, 61932004, 62002343"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"KAUST","award":["URF\/1\/3756-01-01"],"award-info":[{"award-number":["URF\/1\/3756-01-01"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2021,8,14]]},"DOI":"10.1145\/3447548.3467337","type":"proceedings-article","created":{"date-parts":[[2021,8,12]],"date-time":"2021-08-12T06:12:08Z","timestamp":1628748728000},"page":"556-564","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":109,"title":["A Graph-based Approach for Trajectory Similarity Computation in Spatial Networks"],"prefix":"10.1145","author":[{"given":"Peng","family":"Han","sequence":"first","affiliation":[{"name":"King Abdullah University of Science and Technology, Jeddah, Saudi Arabia"}]},{"given":"Jin","family":"Wang","sequence":"additional","affiliation":[{"name":"University of California, Los Angeles, Los Angeles, CA, USA"}]},{"given":"Di","family":"Yao","sequence":"additional","affiliation":[{"name":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"}]},{"given":"Shuo","family":"Shang","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}]},{"given":"Xiangliang","family":"Zhang","sequence":"additional","affiliation":[{"name":"King Abdullah University of Science and Technology, Jeddah, Saudi Arabia"}]}],"member":"320","published-online":{"date-parts":[[2021,8,14]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2010.2048101"},{"key":"e_1_3_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3161602"},{"key":"e_1_3_2_1_3_1","volume-title":"ICLR","author":"Bruna J.","year":"2014","unstructured":"J. Bruna , W. Zaremba , A. Szlam , and Y. LeCun . Spectral networks and locally connected networks on graphs . In ICLR , 2014 . J. Bruna, W. Zaremba, A. Szlam, and Y. LeCun. Spectral networks and locally connected networks on graphs. In ICLR, 2014."},{"key":"e_1_3_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.5555\/1316689.1316758"},{"key":"e_1_3_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1066157.1066213"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE48307.2020.00091"},{"key":"e_1_3_2_1_7_1","volume-title":"ICLR","author":"Chen Y.","year":"2020","unstructured":"Y. Chen , L. Wu , and M. J. Zaki . Reinforcement learning based graph-to-sequence model for natural question generation . In ICLR , 2020 . Y. Chen, L. Wu, and M. J. Zaki. Reinforcement learning based graph-to-sequence model for natural question generation. In ICLR, 2020."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/1807167.1807197"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10500"},{"key":"e_1_3_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2939672.2939754"},{"key":"e_1_3_2_1_11_1","first-page":"1024","volume-title":"NIPS","author":"Hamilton W. L.","year":"2017","unstructured":"W. L. Hamilton , Z. Ying , and J. Leskovec . Inductive representation learning on large graphs . In NIPS , pages 1024 -- 1034 , 2017 . W. L. Hamilton, Z. Ying, and J. Leskovec. Inductive representation learning on large graphs. In NIPS, pages 1024--1034, 2017."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/344"},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2019.00141"},{"key":"e_1_3_2_1_14_1","volume-title":"ICLR","author":"Kingma D. P.","year":"2015","unstructured":"D. P. Kingma and J. Ba . Adam: A method for stochastic optimization . In ICLR , 2015 . D. P. Kingma and J. Ba. Adam: A method for stochastic optimization. In ICLR, 2015."},{"key":"e_1_3_2_1_15_1","volume-title":"ICLR","author":"Kipf T. N.","year":"2017","unstructured":"T. N. Kipf and M. Welling . Semi-supervised classification with graph convolutional networks . In ICLR , 2017 . T. N. Kipf and M. Welling. Semi-supervised classification with graph convolutional networks. In ICLR, 2017."},{"key":"e_1_3_2_1_16_1","first-page":"972","volume-title":"WWW","author":"Li J.","year":"2019","unstructured":"J. Li , Y. Rong , H. Cheng , H. Meng , W. Huang , and J. Huang . Semi-supervised graph classification: A hierarchical graph perspective . In WWW , pages 972 -- 982 , 2019 . J. Li, Y. Rong, H. Cheng, H. Meng, W. Huang, and J. Huang. Semi-supervised graph classification: A hierarchical graph perspective. In WWW, pages 972--982, 2019."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE48307.2020.00037"},{"key":"e_1_3_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2018.00062"},{"key":"e_1_3_2_1_19_1","first-page":"3111","volume-title":"NIPS","author":"Mikolov T.","year":"2013","unstructured":"T. Mikolov , I. Sutskever , K. Chen , G. S. Corrado , and J. Dean . Distributed representations of words and phrases and their compositionality . In NIPS , pages 3111 -- 3119 , 2013 . T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean. Distributed representations of words and phrases and their compositionality. In NIPS, pages 3111--3119, 2013."},{"key":"e_1_3_2_1_20_1","volume-title":"Modeling time series similarity with siamese recurrent networks. CoRR, abs\/1603.04713","author":"Pei W.","year":"2016","unstructured":"W. Pei , D. M. J. Tax , and L. van der Maaten . Modeling time series similarity with siamese recurrent networks. CoRR, abs\/1603.04713 , 2016 . W. Pei, D. M. J. Tax, and L. van der Maaten. Modeling time series similarity with siamese recurrent networks. CoRR, abs\/1603.04713, 2016."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/2339530.2339576"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2017.2685504"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.14778\/3137628.3137630"},{"key":"e_1_3_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2018.2854705"},{"key":"e_1_3_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.14778\/2732939.2732940"},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1145\/3159652.3159656"},{"key":"e_1_3_2_1_27_1","volume-title":"ICLR","author":"Velickovic P.","year":"2018","unstructured":"P. Velickovic , G. Cucurull , A. Casanova , A. Romero , P. Li\u00f2 , and Y. Bengio . Graph attention networks . In ICLR , 2018 . P. Velickovic, G. Cucurull, A. Casanova, A. Romero, P. Li\u00f2, and Y. Bengio. Graph attention networks. In ICLR, 2018."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.5555\/876875.878994"},{"key":"e_1_3_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209978.3209989"},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/CIDM.2009.4938663"},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2019.00123"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.3047070"},{"issue":"2","key":"e_1_3_2_1_33_1","article-title":"Learning deep representation for trajectory clustering","volume":"35","author":"Yao D.","year":"2018","unstructured":"D. Yao , C. Zhang , Z. Zhu , Q. Hu , Z. Wang , J. Huang , and J. Bi . Learning deep representation for trajectory clustering . Expert Syst. J. Knowl. Eng. , 35 ( 2 ), 2018 . D. Yao, C. Zhang, Z. Zhu, Q. Hu, Z. Wang, J. Huang, and J. Bi. Learning deep representation for trajectory clustering. Expert Syst. J. Knowl. Eng., 35(2), 2018.","journal-title":"Expert Syst. J. Knowl. Eng."},{"key":"e_1_3_2_1_34_1","first-page":"201","volume-title":"ICDE","author":"Yi B.","year":"1998","unstructured":"B. Yi , H. V. Jagadish , and C. Faloutsos . Efficient retrieval of similar time sequences under time warping . In ICDE , pages 201 -- 208 , 1998 . B. Yi, H. V. Jagadish, and C. Faloutsos. Efficient retrieval of similar time sequences under time warping. In ICDE, pages 201--208, 1998."},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/444"},{"key":"e_1_3_2_1_36_1","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2020\/445"},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2012.42"},{"issue":"2","key":"e_1_3_2_1_38_1","first-page":"32","article-title":"Geolife: A collaborative social networking service among user, location and trajectory","volume":"33","author":"Zheng Y.","year":"2010","unstructured":"Y. Zheng , X. Xie , and W. Ma . Geolife: A collaborative social networking service among user, location and trajectory . IEEE Data Eng. Bull. , 33 ( 2 ): 32 -- 39 , 2010 . Y. Zheng, X. Xie, and W. Ma. Geolife: A collaborative social networking service among user, location and trajectory. IEEE Data Eng. Bull., 33(2):32--39, 2010.","journal-title":"IEEE Data Eng. Bull."}],"event":{"name":"KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","location":"Virtual Event Singapore","acronym":"KDD '21","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 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3467337","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3447548.3467337","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:18:22Z","timestamp":1750191502000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3447548.3467337"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,14]]},"references-count":38,"alternative-id":["10.1145\/3447548.3467337","10.1145\/3447548"],"URL":"https:\/\/doi.org\/10.1145\/3447548.3467337","relation":{},"subject":[],"published":{"date-parts":[[2021,8,14]]},"assertion":[{"value":"2021-08-14","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}