{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:18:44Z","timestamp":1750220324671,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":30,"publisher":"ACM","license":[{"start":{"date-parts":[[2021,12,14]],"date-time":"2021-12-14T00:00:00Z","timestamp":1639440000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,12,14]]},"DOI":"10.1145\/3486622.3493977","type":"proceedings-article","created":{"date-parts":[[2022,4,14]],"date-time":"2022-04-14T01:18:53Z","timestamp":1649899133000},"page":"595-602","source":"Crossref","is-referenced-by-count":0,"title":["Sequential Patterns for Spatio-Temporal Traffic Prediction"],"prefix":"10.1145","author":[{"given":"Feda","family":"Almuhisen","sequence":"first","affiliation":[{"name":"Laboratoire d'Informatique &amp; Syst\u00e8mes, Aix-Marseille Universit\u00e9, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nicolas","family":"Durand","sequence":"additional","affiliation":[{"name":"Laboratoire d'Informatique &amp; Syst\u00e8mes, Aix-Marseille Universit\u00e9, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leonardo","family":"Brenner","sequence":"additional","affiliation":[{"name":"Laboratoire d'Informatique &amp; Syst\u00e8mes, Aix-Marseille Universit\u00e9, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohamed","family":"Quafafou","sequence":"additional","affiliation":[{"name":"Laboratoire d'Informatique &amp; Syst\u00e8mes, Aix-Marseille Universit\u00e9, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,4,13]]},"reference":[{"volume-title":"ACM SIGMOD Int. Conf. on Management of Data. Washington DC, USA, 207\u2013216","author":"Agrawal R.","unstructured":"R. Agrawal , T. Imielinski , and A. Swami . 1993. Mining association rules between sets of items in large database . In ACM SIGMOD Int. Conf. on Management of Data. Washington DC, USA, 207\u2013216 . R. Agrawal, T. Imielinski, and A. Swami. 1993. Mining association rules between sets of items in large database. In ACM SIGMOD Int. Conf. on Management of Data. Washington DC, USA, 207\u2013216.","key":"e_1_3_2_1_1_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_2_1","DOI":"10.1007\/s41060-017-0076-8"},{"volume-title":"IEEE\/WIC\/ACM International Conference on Web Intelligence (WI)","author":"AlMuhisen F.","unstructured":"F. AlMuhisen , N. Durand , and M. Quafafou . 2018. Sequential Formal Concepts over Time for Trajectory Analysis . In IEEE\/WIC\/ACM International Conference on Web Intelligence (WI) . Santiago, Chile, 598\u2013603. F. AlMuhisen, N. Durand, and M. Quafafou. 2018. Sequential Formal Concepts over Time for Trajectory Analysis. In IEEE\/WIC\/ACM International Conference on Web Intelligence (WI). Santiago, Chile, 598\u2013603.","key":"e_1_3_2_1_3_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_4_1","DOI":"10.1007\/s00779-019-01212-5"},{"volume-title":"PEPS 2007 - Stochastic Automata Networks Software Tool. In 4th Int. Conf. on the Quantitative Evaluation of SysTems (QEST)","author":"Brenner L.","unstructured":"L. Brenner , P. Fernandes , B. Plateau , and I. Sbeity . 2007 . PEPS 2007 - Stochastic Automata Networks Software Tool. In 4th Int. Conf. on the Quantitative Evaluation of SysTems (QEST) . Edimbourgh, UK, 163\u2013164. L. Brenner, P. Fernandes, B. Plateau, and I. Sbeity. 2007. PEPS 2007 - Stochastic Automata Networks Software Tool. In 4th Int. Conf. on the Quantitative Evaluation of SysTems (QEST). Edimbourgh, UK, 163\u2013164.","key":"e_1_3_2_1_5_1"},{"doi-asserted-by":"crossref","unstructured":"E. Cesario C. Comito and D. Talia. 2014. Trajectory data analysis over a cloud-based framework for smart city analytics. Springer 143\u2013162.  E. Cesario C. Comito and D. Talia. 2014. Trajectory data analysis over a cloud-based framework for smart city analytics. Springer 143\u2013162.","key":"e_1_3_2_1_6_1","DOI":"10.1007\/978-3-319-00491-4_8"},{"volume-title":"5th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining","author":"Dong G.","unstructured":"G. Dong and J. Li . 1999. Efficient mining of emerging patterns: Discovering trends and differences . In 5th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining . San Diego, CA, USA, 43\u201352. G. Dong and J. Li. 1999. Efficient mining of emerging patterns: Discovering trends and differences. In 5th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining. San Diego, CA, USA, 43\u201352.","key":"e_1_3_2_1_7_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_8_1","DOI":"10.1007\/978-3-319-46131-1_8"},{"key":"e_1_3_2_1_9_1","first-page":"54","article-title":"A survey of sequential pattern mining","volume":"1","author":"Fournier-Viger P.","year":"2017","unstructured":"P. Fournier-Viger , J.\u00a0 C.-W. Lin , R.\u00a0 U. Kiran , Y.\u00a0 S. Koh , and R. Thomas . 2017 . A survey of sequential pattern mining . Data Science and Pattern Recognition 1 , 1 (2017), 54 \u2013 77 . P. Fournier-Viger, J.\u00a0C.-W. Lin, R.\u00a0U. Kiran, Y.\u00a0S. Koh, and R. Thomas. 2017. A survey of sequential pattern mining. Data Science and Pattern Recognition 1, 1 (2017), 54\u201377.","journal-title":"Data Science and Pattern Recognition"},{"volume-title":"Formal Methods for Mining Structured Objects","author":"Garriga C.","unstructured":"G.\u00a0 C. Garriga . 2013. Lattice theory for sequences . In Formal Methods for Mining Structured Objects . Springer , 21\u201337. G.\u00a0C. Garriga. 2013. Lattice theory for sequences. In Formal Methods for Mining Structured Objects. Springer, 21\u201337.","key":"e_1_3_2_1_10_1"},{"doi-asserted-by":"crossref","unstructured":"A. Jensen. 1953. Markoff chains as an aid in the study of Markoff processes. Scandinavian Actuarial Journal(1953) 87\u201391.  A. Jensen. 1953. Markoff chains as an aid in the study of Markoff processes. Scandinavian Actuarial Journal(1953) 87\u201391.","key":"e_1_3_2_1_11_1","DOI":"10.1080\/03461238.1953.10419459"},{"volume-title":"Spatiotemporal Periodical Pattern Mining in Traffic Data. In 2nd ACM SIGKDD International Workshop on Urban Computing","author":"Jindal T.","unstructured":"T. Jindal , P. Giridhar , L.-A. Tang , J. Li , and J. Han . 2003 . Spatiotemporal Periodical Pattern Mining in Traffic Data. In 2nd ACM SIGKDD International Workshop on Urban Computing . Chicago, Illinois, USA, 1\u20138. T. Jindal, P. Giridhar, L.-A. Tang, J. Li, and J. Han. 2003. Spatiotemporal Periodical Pattern Mining in Traffic Data. In 2nd ACM SIGKDD International Workshop on Urban Computing. Chicago, Illinois, USA, 1\u20138.","key":"e_1_3_2_1_12_1"},{"volume-title":"Int. Conf. on Intelligent Transportation Systems (ITSC)","author":"Lassoued Y.","unstructured":"Y. Lassoued , J. Monteil , Y. Gu , G. Russo , R. Shorten , and M. Mevissen . 2017. A Hidden Markov Model for Route and Destination Prediction . In Int. Conf. on Intelligent Transportation Systems (ITSC) . Yokohama, Japan. Y. Lassoued, J. Monteil, Y. Gu, G. Russo, R. Shorten, and M. Mevissen. 2017. A Hidden Markov Model for Route and Destination Prediction. In Int. Conf. on Intelligent Transportation Systems (ITSC). Yokohama, Japan.","key":"e_1_3_2_1_13_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_14_1","DOI":"10.1016\/j.pmcj.2013.06.005"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_15_1","DOI":"10.1016\/j.procs.2019.09.226"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_16_1","DOI":"10.1016\/j.pmcj.2018.07.004"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_17_1","DOI":"10.1109\/MCOM.2013.6525604"},{"unstructured":"M. Piorkowski N. Sarafijanovic-Djukic and M. Grossglauser. 2009. CRAWDAD dataset epfl\/mobility (v. 2009-02-24). https:\/\/crawdad.org\/epfl\/mobility\/20090224\/cab. traceset: cab.  M. Piorkowski N. Sarafijanovic-Djukic and M. Grossglauser. 2009. CRAWDAD dataset epfl\/mobility (v. 2009-02-24). https:\/\/crawdad.org\/epfl\/mobility\/20090224\/cab. traceset: cab.","key":"e_1_3_2_1_18_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_19_1","DOI":"10.1007\/978-1-4757-4828-4_5"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_20_1","DOI":"10.1016\/j.trc.2014.02.007"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_21_1","DOI":"10.1109\/TITS.2019.2899179"},{"volume-title":"Introduction to the numerical solution of Markov chains","author":"Stewart J.","unstructured":"W.\u00a0 J. Stewart . 1994. Introduction to the numerical solution of Markov chains . Princeton University Press . W.\u00a0J. Stewart. 1994. Introduction to the numerical solution of Markov chains. Princeton University Press.","key":"e_1_3_2_1_22_1"},{"key":"e_1_3_2_1_23_1","article-title":"Mining Evolution Patterns from Complex Trajectory Structures","volume":"9","author":"Wang H.","year":"2020","unstructured":"H. Wang , Y. Du , J. Yi , N. Wang , and F. Liang . 2020 . Mining Evolution Patterns from Complex Trajectory Structures . ISPRS Int. Journal of Geo-Information 9 , 7 (2020). H. Wang, Y. Du, J. Yi, N. Wang, and F. Liang. 2020. Mining Evolution Patterns from Complex Trajectory Structures. ISPRS Int. Journal of Geo-Information 9, 7 (2020).","journal-title":"Journal of Geo-Information"},{"volume-title":"14th International Conference on Communication Technology","author":"Wang L.","unstructured":"L. Wang , K. Hu , T. Ku , and J. Wu . 2012. Discovering closed frequent patterns in moving trajectory database . In 14th International Conference on Communication Technology . Chengdu, China, 567\u2013572. L. Wang, K. Hu, T. Ku, and J. Wu. 2012. Discovering closed frequent patterns in moving trajectory database. In 14th International Conference on Communication Technology. Chengdu, China, 567\u2013572.","key":"e_1_3_2_1_24_1"},{"key":"e_1_3_2_1_25_1","first-page":"63","article-title":"A Survey of Traffic Prediction: from Spatio-Temporal Data to Intelligent Transportation. Data Sci","volume":"6","author":"Yuan H.","year":"2021","unstructured":"H. Yuan and G. Li . 2021 . A Survey of Traffic Prediction: from Spatio-Temporal Data to Intelligent Transportation. Data Sci . Eng. 6 (2021), 63 \u2013 85 . H. Yuan and G. Li. 2021. A Survey of Traffic Prediction: from Spatio-Temporal Data to Intelligent Transportation. Data Sci. Eng. 6(2021), 63\u201385.","journal-title":"Eng."},{"volume-title":"Int. Conf. on Advances in Geographic Information Systems","author":"Yuan J.","unstructured":"N.\u00a0 J. Yuan , Y. Zheng , C. Zhang , W. Xie , X. Xie , G. Sun , and Y. Huang . 2010. T-drive: Driving directions based on taxi trajectories . In Int. Conf. on Advances in Geographic Information Systems . San Jose, California, USA, 99\u2013108. N.\u00a0J. Yuan, Y. Zheng, C. Zhang, W. Xie, X. Xie, G. Sun, and Y. Huang. 2010. T-drive: Driving directions based on taxi trajectories. In Int. Conf. on Advances in Geographic Information Systems. San Jose, California, USA, 99\u2013108.","key":"e_1_3_2_1_26_1"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_27_1","DOI":"10.1016\/j.asej.2019.10.006"},{"key":"e_1_3_2_1_28_1","first-page":"1216","article-title":"A research on driving condition prediction for HEVs based on Markov chain","volume":"36","author":"Zhang X.","year":"2014","unstructured":"X. Zhang , S. Wang , and Y. Tian . 2014 . A research on driving condition prediction for HEVs based on Markov chain . Automotive Engineering 36 , 10 (2014), 1216 \u2013 1220 . X. Zhang, S. Wang, and Y. Tian. 2014. A research on driving condition prediction for HEVs based on Markov chain. Automotive Engineering 36, 10 (2014), 1216\u20131220.","journal-title":"Automotive Engineering"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_29_1","DOI":"10.1088\/1742-6596\/1168\/5\/052001"},{"doi-asserted-by":"publisher","key":"e_1_3_2_1_30_1","DOI":"10.1145\/2743025"}],"event":{"sponsor":["SIGAI ACM Special Interest Group on Artificial Intelligence"],"acronym":"WI-IAT '21","name":"WI-IAT '21: IEEE\/WIC\/ACM International Conference on Web Intelligence","location":"ESSENDON VIC Australia"},"container-title":["IEEE\/WIC\/ACM International Conference on Web Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3486622.3493977","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3486622.3493977","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T20:12:05Z","timestamp":1750191125000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3486622.3493977"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,12,14]]},"references-count":30,"alternative-id":["10.1145\/3486622.3493977","10.1145\/3486622"],"URL":"https:\/\/doi.org\/10.1145\/3486622.3493977","relation":{},"subject":[],"published":{"date-parts":[[2021,12,14]]}}}