{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,4]],"date-time":"2024-10-04T04:24:26Z","timestamp":1728015866567},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2022,9,12]],"date-time":"2022-09-12T00:00:00Z","timestamp":1662940800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,9,12]],"date-time":"2022-09-12T00:00:00Z","timestamp":1662940800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Front. Comput. Sci."],"published-print":{"date-parts":[[2023,6]]},"DOI":"10.1007\/s11704-022-1623-6","type":"journal-article","created":{"date-parts":[[2022,9,12]],"date-time":"2022-09-12T09:02:56Z","timestamp":1662973376000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Exploring the tidal effect of urban business district with large-scale human mobility data"],"prefix":"10.1007","volume":"17","author":[{"given":"Hongting","family":"Niu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ying","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hengshu","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cong","family":"Geng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiuchun","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bo","family":"Lang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,12]]},"reference":[{"issue":"6","key":"1623_CR1","first-page":"1125","volume":"34","author":"F Wang","year":"2015","unstructured":"Wang F, Gao X, Xu Z. Identification and classification of urban commercial districts at block scale. Geographical Research, 2015, 34(6): 1125\u20131134","journal-title":"Geographical Research"},{"issue":"1\u20132","key":"1623_CR2","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1016\/j.landurbplan.2004.12.005","volume":"75","author":"J Xiao","year":"2006","unstructured":"Xiao J, Shen Y, Ge J, Tateishi R, Tang C, Liang Y, Huang Z. Evaluating urban expansion and land use change in Shijiazhuang, China, by using GIS and remote sensing. Landscape and Urban Planning, 2006, 75(1\u20132): 69\u201380","journal-title":"Landscape and Urban Planning"},{"unstructured":"Institute D D. 2018 China Urban Business Circle Travel and Consumption Analysis Report. Business district radiation map drawn by didi travel big data. See 199it website, 2018","key":"1623_CR3"},{"unstructured":"Red Star News. Schematic diagram of the distribution of Chengdu\u2019s business districts and the density levels of business districts. See Sohu website, 2020","key":"1623_CR4"},{"issue":"5","key":"1623_CR5","doi-asserted-by":"publisher","first-page":"604","DOI":"10.1145\/324133.324140","volume":"46","author":"J M Kleinberg","year":"1999","unstructured":"Kleinberg J M. Authoritative sources in a hyperlinked environment. Journal of ACM, 1999, 46(5): 604\u2013632","journal-title":"Journal of ACM"},{"unstructured":"Shi X, Chen Z, Wang H, Yeung D Y, Wong W K, Woo W C. Convolutional LSTM network: a machine learning approach for precipitation nowcasting. In: Proceedings of the 28th International Conference on Neural Information Processing Systems. 2015, 802\u2013810","key":"1623_CR6"},{"issue":"3","key":"1623_CR7","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1109\/TKDE.2014.2345405","volume":"27","author":"N J Yuan","year":"2015","unstructured":"Yuan N J, Zheng Y, Xie X, Wang Y, Zheng K, Xiong H. Discovering urban functional zones using latent activity trajectories. IEEE Transactions on Knowledge and Data Engineering, 2015, 27(3): 712\u2013725","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"unstructured":"Graves A, Jaitly N. Towards end-to-end speech recognition with recurrent neural networks. In: Proceedings of the 31st International Conference on International Conference on Machine Learning. 2014, II-1764-II-1772","key":"1623_CR8"},{"issue":"1","key":"1623_CR9","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1145\/3465059","volume":"13","author":"H Niu","year":"2022","unstructured":"Niu H, Zhu H, Sun Y, Lu X, Sun J, Zhao Z, Xiong H, Lang B. Exploring the risky travel area and behavior of car-hailing service. ACM Transactions on Intelligent Systems and Technology, 2022, 13(1): 9","journal-title":"ACM Transactions on Intelligent Systems and Technology"},{"unstructured":"Ke G, Meng Q, Finley T, Wang T, Chen W, Ma W, Ye Q, Liu T Y. LightGBM: a highly efficient gradient boosting decision tree. In: Proceedings of the 31st International Conference on Neural Information Processing Systems. 2017, 3149\u20133157","key":"1623_CR10"},{"issue":"1","key":"1623_CR11","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.ijar.2006.01.002","volume":"43","author":"A P\u00e9rez","year":"2006","unstructured":"P\u00e9rez A, Larra\u00f1aga P, Inza I. Supervised classification with conditional Gaussian networks: increasing the structure complexity from naive Bayes. International Journal of Approximate Reasoning, 2006, 43(1): 1\u201325","journal-title":"International Journal of Approximate Reasoning"},{"doi-asserted-by":"crossref","unstructured":"Dumont M, Mar\u00e9e R, Wehenkel L, Geurts P. Fast multi-class image annotation with random subwindows and multiple output randomized trees. In: Proceedings of the 4th International Conference on Computer Vision Theory and Applications. 2009, 196\u2013203","key":"1623_CR12","DOI":"10.5220\/0001800001960203"},{"issue":"1","key":"1623_CR13","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1023\/A:1010933404324","volume":"45","author":"L Breiman","year":"2001","unstructured":"Breiman L. Random forests. Machine Learning, 2001, 45(1): 5\u201332","journal-title":"Machine Learning"},{"issue":"3","key":"1623_CR14","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1023\/A:1018628609742","volume":"9","author":"J A K Suykens","year":"1999","unstructured":"Suykens J A K, Vandewalle J. Least squares support vector machine classifiers. Neural Processing Letters, 1999, 9(3): 293\u2013300","journal-title":"Neural Processing Letters"},{"issue":"1\u20132","key":"1623_CR15","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1007\/s10107-016-1030-6","volume":"162","author":"M Schmidt","year":"2017","unstructured":"Schmidt M, Le Roux N, Bach F. Minimizing finite sums with the stochastic average gradient. Mathematical Programming, 2017, 162(1\u20132): 83\u2013112","journal-title":"Mathematical Programming"},{"key":"1623_CR16","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, Vanderplas J, Passos A, Cournapeau D, Brucher M, Perrot M, Duchesnay \u00c9. Scikit-learn: machine learning in python. The Journal of Machine Learning Research, 2011, 12: 2825\u20132830","journal-title":"The Journal of Machine Learning Research"},{"key":"1623_CR17","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.jtrangeo.2015.04.008","volume":"45","author":"W Yu","year":"2015","unstructured":"Yu W, Ai T, Shao S. The analysis and delimitation of Central Business District using network kernel density estimation. Journal of Transport Geography, 2015, 45: 32\u201347","journal-title":"Journal of Transport Geography"},{"issue":"1","key":"1623_CR18","doi-asserted-by":"publisher","first-page":"81","DOI":"10.2307\/3144521","volume":"39","author":"D L Huff","year":"1963","unstructured":"Huff D L. A probabilistic analysis of shopping center trade areas. Land Economics, 1963, 39(1): 81\u201390","journal-title":"Land Economics"},{"issue":"5","key":"1623_CR19","first-page":"56","volume":"33","author":"B Hao","year":"2017","unstructured":"Hao B, Dong S, Hu Y C, Liu X, Gao Y J, Zhang Y D. Urban business zones delimitation method based on the fusion of multidimensional characteristics. Geography and Geo-Information Science, 2017, 33(5): 56\u201362","journal-title":"Geography and Geo-Information Science"},{"doi-asserted-by":"crossref","unstructured":"Qi G, Li X, Li S, Pan G, Wang Z, Zhang D. Measuring social functions of city regions from large-scale taxi behaviors. In: Proceedings of 2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops). 2011, 384\u2013388","key":"1623_CR20","DOI":"10.1109\/PERCOMW.2011.5766912"},{"doi-asserted-by":"crossref","unstructured":"Yuan J, Zheng Y, Xie X. Discovering regions of different functions in a city using human mobility and POIs. In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2012, 186\u2013194","key":"1623_CR21","DOI":"10.1145\/2339530.2339561"},{"key":"1623_CR22","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1016\/j.trc.2015.06.007","volume":"58","author":"H Dong","year":"2015","unstructured":"Dong H, Wu M, Ding X, Chu L, Jia L, Qin Y, Zhou X. Traffic zone division based on big data from mobile phone base stations. Transportation Research Part C: Emerging Technologies, 2015, 58: 278\u2013291","journal-title":"Transportation Research Part C: Emerging Technologies"},{"issue":"1","key":"1623_CR23","doi-asserted-by":"publisher","first-page":"73","DOI":"10.1016\/j.landurbplan.2012.02.012","volume":"106","author":"Y Liu","year":"2012","unstructured":"Liu Y, Wang F, Xiao Y, Gao S. Urban land uses and traffic \u2018source-sink areas\u2019: evidence from GPS-enabled taxi data in Shanghai. Landscape and Urban Planning, 2012, 106(1): 73\u201387","journal-title":"Landscape and Urban Planning"},{"issue":"1","key":"1623_CR24","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1109\/TITS.2012.2209201","volume":"14","author":"G Pan","year":"2013","unstructured":"Pan G, Qi G, Wu Z, Zhang D, Li S. Land-use classification using taxi GPS traces. IEEE Transactions on Intelligent Transportation Systems, 2013, 14(1): 113\u2013123","journal-title":"IEEE Transactions on Intelligent Transportation Systems"},{"doi-asserted-by":"crossref","unstructured":"Zhang P, Bao Z, Li Y, Li G, Zhang Y, Peng Z. Trajectory-driven influential billboard placement. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2018, 2748\u20132757","key":"1623_CR25","DOI":"10.1145\/3219819.3219946"},{"doi-asserted-by":"crossref","unstructured":"Sun Y, Zhu H, Zhuang F, Gu J, He Q. Exploring the urban region-of-interest through the analysis of online map search queries. In: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. 2018, 2269\u20132278","key":"1623_CR26","DOI":"10.1145\/3219819.3220009"},{"issue":"2","key":"1623_CR27","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1145\/3440207","volume":"54","author":"S Wang","year":"2022","unstructured":"Wang S, Bao Z, Culpepper J S, Cong G. A survey on trajectory data management, analytics, and learning. ACM Computing Surveys, 2022, 54(2): 39","journal-title":"ACM Computing Surveys"},{"issue":"16","key":"1623_CR28","doi-asserted-by":"publisher","first-page":"4571","DOI":"10.3390\/s20164571","volume":"20","author":"D Wang","year":"2020","unstructured":"Wang D, Miwa T, Morikawa T. Big trajectory data mining: a survey of methods, applications, and services. Sensors, 2020, 20(16): 4571","journal-title":"Sensors"},{"doi-asserted-by":"crossref","unstructured":"Lu M, Wang Z, Yuan X. TrajRank: exploring travel behaviour on a route by trajectory ranking. In: Proceedings of 2015 IEEE Pacific Visualization Symposium (PacificVis). 2015, 311\u2013318","key":"1623_CR29","DOI":"10.1109\/PACIFICVIS.2015.7156392"},{"doi-asserted-by":"crossref","unstructured":"Zheng Y, Zhao G, Liu J. A novel grid based k-means cluster method for traffic zone division. In: Proceedings of the 2nd International Conference on Cloud Computing and Big Data. 2015, 165\u2013178","key":"1623_CR30","DOI":"10.1007\/978-3-319-28430-9_13"},{"issue":"6","key":"1623_CR31","doi-asserted-by":"publisher","first-page":"1193","DOI":"10.1007\/s12650-019-00600-6","volume":"22","author":"G Sun","year":"2019","unstructured":"Sun G, Chang B, Zhu L, Wu H, Zheng K, Liang R. TZVis: visual analysis of bicycle data for traffic zone division. Journal of Visualization, 2019, 22(6): 1193\u20131208","journal-title":"Journal of Visualization"},{"key":"1623_CR32","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.jvlc.2017.09.005","volume":"43","author":"Y Miyagi","year":"2017","unstructured":"Miyagi Y, Onishi M, Watanabe C, Itoh T, Takatsuka M. Classification and visualization for symbolic people flow data. Journal of Visual Languages & Computing, 2017, 43: 91\u2013102","journal-title":"Journal of Visual Languages & Computing"},{"doi-asserted-by":"crossref","unstructured":"Ren H, Ruan S, Li Y, Bao J, Meng C, Li R, Zheng Y. MtrajRec: map-constrained trajectory recovery via Seq2Seq multi-task learning. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2021, 1410\u20131419","key":"1623_CR33","DOI":"10.1145\/3447548.3467238"},{"doi-asserted-by":"crossref","unstructured":"Han P, Wang J, Yao D, Shang S, Zhang X. A graph-based approach for trajectory similarity computation in spatial networks. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 2021, 556\u2013564","key":"1623_CR34","DOI":"10.1145\/3447548.3467337"},{"issue":"7","key":"1623_CR35","doi-asserted-by":"publisher","first-page":"313","DOI":"10.3390\/ijgi8070313","volume":"8","author":"H Wu","year":"2019","unstructured":"Wu H, Liu L, Yu Y, Peng Z, Jiao H, Niu Q. An agent-based model simulation of human mobility based on mobile phone data: how commuting relates to congestion. ISPRS International Journal of Geo-Information, 2019, 8(7): 313","journal-title":"ISPRS International Journal of Geo-Information"},{"doi-asserted-by":"crossref","unstructured":"Chen X, Wang J, Xie K. TrafficStream: a streaming traffic flow forecasting framework based on graph neural networks and continual learning. In: Proceedings of the 30th International Joint Conference on Artificial Intelligence. 2021, 3620\u20133626","key":"1623_CR36","DOI":"10.24963\/ijcai.2021\/498"},{"doi-asserted-by":"crossref","unstructured":"Fang Z, Long Q, Song G, Xie K. Spatial-temporal graph ODE networks for traffic flow forecasting. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 2021, 364\u2013373","key":"1623_CR37","DOI":"10.1145\/3447548.3467430"},{"doi-asserted-by":"publisher","unstructured":"Wan H, Lin Y, Guo S, Lin Y. Pre-training time-aware location embeddings from spatial-temporal trajectories. IEEE Transactions on Knowledge and Data Engineering, 2021, DOI: https:\/\/doi.org\/10.1109\/TKDE.2021.3057875","key":"1623_CR38","DOI":"10.1109\/TKDE.2021.3057875"},{"doi-asserted-by":"crossref","unstructured":"Cao C, Li M. Generating mobility trajectories with retained data utility. In: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 2021, 2610\u20132620","key":"1623_CR39","DOI":"10.1145\/3447548.3467158"},{"issue":"1","key":"1623_CR40","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1145\/2031331.2031335","volume":"13","author":"C Y Chow","year":"2011","unstructured":"Chow C Y, Mokbel M F. Trajectory privacy in location-based services and data publication. ACM SIGKDD Explorations Newsletter, 2011, 13(1): 19\u201329","journal-title":"ACM SIGKDD Explorations Newsletter"},{"doi-asserted-by":"crossref","unstructured":"Kim Y, Han J, Yuan C. TOPTRAC: topical trajectory pattern mining. In: Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 2015, 587\u2013596","key":"1623_CR41","DOI":"10.1145\/2783258.2783342"},{"issue":"13","key":"1623_CR42","doi-asserted-by":"publisher","first-page":"2073","DOI":"10.14778\/3151106.3151111","volume":"10","author":"D W Choi","year":"2017","unstructured":"Choi D W, Pei J, Heinis T. Efficient mining of regional movement patterns in semantic trajectories. Proceedings of the VLDB Endowment, 2017, 10(13): 2073\u20132084","journal-title":"Proceedings of the VLDB Endowment"}],"container-title":["Frontiers of Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11704-022-1623-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11704-022-1623-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11704-022-1623-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T17:48:17Z","timestamp":1727977697000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11704-022-1623-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,12]]},"references-count":42,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["1623"],"URL":"https:\/\/doi.org\/10.1007\/s11704-022-1623-6","relation":{},"ISSN":["2095-2228","2095-2236"],"issn-type":[{"type":"print","value":"2095-2228"},{"type":"electronic","value":"2095-2236"}],"subject":[],"published":{"date-parts":[[2022,9,12]]},"assertion":[{"value":"1 November 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 March 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 September 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"173319"}}