{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T22:20:45Z","timestamp":1743114045579,"version":"3.40.3"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030676667"},{"type":"electronic","value":"9783030676674"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-67667-4_17","type":"book-chapter","created":{"date-parts":[[2021,2,24]],"date-time":"2021-02-24T07:10:26Z","timestamp":1614150626000},"page":"275-290","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["A Route-Affecting Region Based Approach for Feature Extraction in Transportation Route Planning"],"prefix":"10.1007","author":[{"given":"Fandel","family":"Lin","sequence":"first","affiliation":[]},{"given":"Hsun-Ping","family":"Hsieh","sequence":"additional","affiliation":[]},{"given":"Jie-Yu","family":"Fang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,2,25]]},"reference":[{"issue":"1","key":"17_CR1","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1016\/j.jtrangeo.2004.11.003","volume":"13","author":"L Steg","year":"2005","unstructured":"Steg, L., Gifford, R.: Sustainable transportation and quality of life. J. Transp. Geogr. 13(1), 59\u201369 (2005)","journal-title":"J. Transp. Geogr."},{"key":"17_CR2","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.trb.2015.03.006","volume":"77","author":"H Cancela","year":"2015","unstructured":"Cancela, H., Mauttone, A., Urquhart, M.E.: Mathematical programming formulations for transit network design. Transp. Res. Part B: Methodol. 77, 17\u201337 (2015)","journal-title":"Transp. Res. Part B: Methodol."},{"key":"17_CR3","doi-asserted-by":"publisher","first-page":"2440","DOI":"10.1016\/j.cor.2008.09.014","volume":"36","author":"A Mauttone","year":"2009","unstructured":"Mauttone, A., Urquhart, M.E.: A route set construction algorithm for the transit network design problem. Comput. Oper. Res. 36, 2440\u20132449 (2009)","journal-title":"Comput. Oper. Res."},{"key":"17_CR4","first-page":"276","volume":"77","author":"M Pternea","year":"2015","unstructured":"Pternea, M., Kepaptsoglou, K., Karlaftis, M.G.: Sustainable urban transit network design. Transp. Res. Part A: Policy Pract. 77, 276\u2013291 (2015)","journal-title":"Transp. Res. Part A: Policy Pract."},{"issue":"10","key":"17_CR5","doi-asserted-by":"publisher","first-page":"922","DOI":"10.1016\/j.trb.2009.04.003","volume":"43","author":"L Quadrifoglio","year":"2009","unstructured":"Quadrifoglio, L., Li, X.: A methodology to derive the critical demand density for designing and operating feeder transit services. Transp. Res. Part B: Methodol. 43(10), 922\u2013935 (2009)","journal-title":"Transp. Res. Part B: Methodol."},{"issue":"2","key":"17_CR6","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/j.ejor.2010.08.020","volume":"209","author":"WY Szeto","year":"2011","unstructured":"Szeto, W.Y., Wu, Y.: A simultaneous bus route design and frequency setting problem for Tin Shui Wai, Hong Kong. Eur. J. Oper. Res. 209(2), 141\u2013155 (2011)","journal-title":"Eur. J. Oper. Res."},{"issue":"1","key":"17_CR7","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1016\/j.cie.2010.02.005","volume":"59","author":"V Guihaire","year":"2010","unstructured":"Guihaire, V., Hao, J.-K.: Transit network timetabling and vehicle assignment for regulating authorities. Comput. Ind. Eng. 59(1), 16\u201323 (2010)","journal-title":"Comput. Ind. Eng."},{"key":"17_CR8","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.trc.2012.05.006","volume":"25","author":"Y Yan","year":"2012","unstructured":"Yan, Y., Meng, Q., Wang, S., Guo, X.: Robust optimization model of schedule design for a fixed bus route. Transp. Res. Part C: Emerg. Technol. 25, 113\u2013121 (2012)","journal-title":"Transp. Res. Part C: Emerg. Technol."},{"issue":"5","key":"17_CR9","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1061\/(ASCE)0733-947X(2002)128:5(429)","volume":"128","author":"SI-J Chien","year":"2002","unstructured":"Chien, S.I.-J., Ding, Y., Wei, C.: Dynamic bus arrival time prediction with artificial neural networks. J. Transp. Eng. 128(5), 429\u2013438 (2002)","journal-title":"J. Transp. Eng."},{"key":"17_CR10","doi-asserted-by":"publisher","first-page":"1133","DOI":"10.1061\/(ASCE)TE.1943-5436.0000589","volume":"139","author":"Y Lin","year":"2013","unstructured":"Lin, Y., Yang, X., Zou, N., Jia, L.: Real-time bus arrival time prediction: case study for Jinan, China. J. Transp. Eng. 139, 1133\u20131140 (2013)","journal-title":"J. Transp. Eng."},{"key":"17_CR11","doi-asserted-by":"publisher","unstructured":"Cheng, S., Liu, B., Zhai, B.: Bus arrival time prediction model based on APC data. In: the 6th Advanced Forum on Transportation of China (2010). https:\/\/doi.org\/10.1049\/cp.2010.1123","DOI":"10.1049\/cp.2010.1123"},{"key":"17_CR12","doi-asserted-by":"publisher","unstructured":"Arabghalizi, T., Labrinidis, A.: How full will my next bus be? A framework to predict bus crowding levels. In: Proceedings of the 8th International Workshop on Urban Computing. ACM, Anchorage (2019). https:\/\/doi.org\/10.13140\/RG.2.2.12969.75368","DOI":"10.13140\/RG.2.2.12969.75368"},{"key":"17_CR13","doi-asserted-by":"publisher","DOI":"10.1080\/23249935.2018.1537319","author":"M Yap","year":"2018","unstructured":"Yap, M., Cats, O., Arem, B.: Crowding valuation in urban tram and bus transportation based on smart card data. Transp.: Transp. Sci. (2018). https:\/\/doi.org\/10.1080\/23249935.2018.1537319","journal-title":"Transp.: Transp. Sci."},{"key":"17_CR14","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.trc.2011.06.009","volume":"21","author":"Y Wei","year":"2012","unstructured":"Wei, Y., Chen, M.-C.: Forecasting the short-term metro passenger flow with empirical mode decomposition and neural networks. Transp. Res. Part C 21, 148\u2013162 (2012)","journal-title":"Transp. Res. Part C"},{"key":"17_CR15","doi-asserted-by":"publisher","unstructured":"Chen, Q., Li, C., Guo, W.: Railway passenger volume forecast based on IPSO-BP neural network. In: International Conference on Information Technology and Computer Science (2009). https:\/\/doi.org\/10.1109\/ITCS.2009.187","DOI":"10.1109\/ITCS.2009.187"},{"key":"17_CR16","doi-asserted-by":"crossref","unstructured":"Lin, F., Hsieh, H.-P.: An intelligent and interactive route planning maker for deploying new transportation services. In: The proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 620\u2013621 (2018)","DOI":"10.1145\/3274895.3282801"},{"key":"17_CR17","doi-asserted-by":"publisher","unstructured":"Mo, Y., Su, Y.: Neural networks based real-time transit passenger volume prediction. In: The 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS) (2009). https:\/\/doi.org\/10.1109\/PEITS.2009.5406782","DOI":"10.1109\/PEITS.2009.5406782"},{"issue":"3","key":"17_CR18","first-page":"239","volume":"31","author":"K Nam","year":"1995","unstructured":"Nam, K., Schaefer, T.: Forecasting international airline passenger traffic using neural networks. Logist. Transp. Rev. 31(3), 239 (1995)","journal-title":"Logist. Transp. Rev."},{"key":"17_CR19","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/j.neucom.2015.03.085","volume":"166","author":"Y Sun","year":"2015","unstructured":"Sun, Y., Leng, B., Guan, W.: A novel wavelet-SVM short-time passenger flow prediction in Beijing subway system. Neurocomputing 166, 109\u2013121 (2015)","journal-title":"Neurocomputing"},{"issue":"2","key":"17_CR20","doi-asserted-by":"publisher","first-page":"3728","DOI":"10.1016\/j.eswa.2008.02.071","volume":"36","author":"T-H Tsai","year":"2009","unstructured":"Tsai, T.-H., Lee, C.-K., Wei, C.-H.: Neural network based temporal feature models for short-term railway passenger demand forecasting. Expert Syst. Appl. 36(2), 3728\u20133736 (2009)","journal-title":"Expert Syst. Appl."},{"issue":"2","key":"17_CR21","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1016\/0305-0548(74)90046-X","volume":"1","author":"LA Silman","year":"1974","unstructured":"Silman, L.A., Barzily, Z., Passy, U.: Planning the route system for urban buses. Comput. Oper. Res. 1(2), 201\u2013211 (1974)","journal-title":"Comput. Oper. Res."},{"issue":"2","key":"17_CR22","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/S0191-2615(97)00016-7","volume":"32","author":"H Yang","year":"1998","unstructured":"Yang, H., Zhou, J.: Optimal traffic counting locations for origin-destination matrix estimation. Transp. Res. Part B: Methodol. 32(2), 109\u2013126 (1998)","journal-title":"Transp. Res. Part B: Methodol."},{"key":"17_CR23","unstructured":"Peterson, A.: The origin-destination matrix estimation problem - analysis and computations. Doctoral dissertation, Department of Science and Technology. Linkoping University, Sweden (2007). urn:nbn:se:liu:diva-8859"},{"key":"17_CR24","unstructured":"Su H.-M., Kuan, C.-C.: Planning and design guidelines. In: Design Manual for Urban Sidewalks, vol. 4, no. 1, pp. 1\u20134 (2003)"},{"issue":"1","key":"17_CR25","first-page":"12","volume":"2","author":"TM Cover","year":"1991","unstructured":"Cover, T.M., Thomas, J.A.: Entropy, relative entropy and mutual information. Elem. Inf. Theory 2(1), 12\u201313 (1991)","journal-title":"Elem. Inf. Theory"}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases: Applied Data Science Track"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-67667-4_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,23]],"date-time":"2025-02-23T23:04:47Z","timestamp":1740351887000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-67667-4_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030676667","9783030676674"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-67667-4_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"25 February 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ghent","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Belgium","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ecmlpkdd2020.net\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"945","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"195","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"21% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4,5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4,4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference took place virtually due to the COVID-19 pandemic","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}