{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T20:03:12Z","timestamp":1743019392756,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031308543"},{"type":"electronic","value":"9783031308550"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-30855-0_1","type":"book-chapter","created":{"date-parts":[[2023,4,27]],"date-time":"2023-04-27T10:02:50Z","timestamp":1682589770000},"page":"3-22","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Analysis of the Tourist\u2019s Behavior in Lisbon Using Data from a Mobile Operator"],"prefix":"10.1007","author":[{"given":"Bruno","family":"Francisco","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2058-693X","authenticated-orcid":false,"given":"Ricardo","family":"Ribeiro","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1075-0177","authenticated-orcid":false,"given":"Fernando","family":"Batista","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6662-0806","authenticated-orcid":false,"given":"Jo\u00e3o","family":"Ferreira","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,4,28]]},"reference":[{"key":"1_CR1","unstructured":"LISBONEIDEE Homepage. http:\/\/www.lisbonne-idee.pt\/p5358-lisboa-recebe-mais-turistas-poresidente-que-londres.html. Accessed 23 July 2022"},{"key":"1_CR2","unstructured":"C\u00e2mara Municipal de Lisboa Homepage. https:\/\/www.lisboa.pt\/. Accessed 23 July 2022"},{"key":"1_CR3","unstructured":"LxDataLab Homepage. https:\/\/lisboainteligente.cm-lisboa.pt\/. Accessed 23 July 2022"},{"key":"1_CR4","unstructured":"Secretaria Geral da Economia Homepage. https:\/\/www.sgeconomia.gov.pt\/noticias\/portugal-e-o-5-pais-com-mais-forte-contributo-do-turismo-para-o-pib.aspx. Accessed 24 July 2022"},{"issue":"4","key":"1_CR5","doi-asserted-by":"publisher","first-page":"1671","DOI":"10.1007\/s11116-020-10108-w","volume":"48","author":"M Fekih","year":"2020","unstructured":"Fekih, M., Bellemans, T., Smoreda, Z., Bonnel, P., Furno, A., Galland, S.: A data-driven approach for origin\u2013destination matrix construction from cellular network signalling data: a case study of Lyon region (France). Transportation 48(4), 1671\u20131702 (2020). https:\/\/doi.org\/10.1007\/s11116-020-10108-w","journal-title":"Transportation"},{"issue":"2","key":"1_CR6","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1080\/23270012.2020.1741039","volume":"7","author":"E Carter","year":"2020","unstructured":"Carter, E., Adam, P., Tsakis, D., Shaw, S., Watson, R., Ryan, P.: Enhancing pedestrian mobility in smart cities using big data. J. Manag. Anal. 7(2), 173\u2013188 (2020). https:\/\/doi.org\/10.1080\/23270012.2020.1741039","journal-title":"J. Manag. Anal."},{"issue":"1","key":"1_CR7","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/s11042-021-10993-y","volume":"81","author":"C Badii","year":"2021","unstructured":"Badii, C., Difino, A., Nesi, P., Paoli, I., Paolucci, M.: Classification of users\u2019 transportation modalities from mobiles in real operating conditions. Multimed. Tools Appl. 81(1), 115\u2013140 (2021). https:\/\/doi.org\/10.1007\/s11042-021-10993-y","journal-title":"Multimed. Tools Appl."},{"key":"1_CR8","doi-asserted-by":"publisher","unstructured":"Haidery, S.A., Ullah, H., Ullah Khan, N., Fatima, K., Shahla Rizvi, S., Kwon, S.J.: Role of big data in the development of smart city by analyzing the density of residents in Shanghai. Electron. Switz. 9(5) (2020). https:\/\/doi.org\/10.3390\/electronics9050837","DOI":"10.3390\/electronics9050837"},{"issue":"1","key":"1_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1140\/epjds\/s13688-018-0168-2","volume":"7","author":"C Mizzi","year":"2018","unstructured":"Mizzi, C., et al.: Unraveling pedestrian mobility on a road network using ICTs data during great tourist events. EPJ Data Science 7(1), 1\u201321 (2018). https:\/\/doi.org\/10.1140\/epjds\/s13688-018-0168-2","journal-title":"EPJ Data Science"},{"issue":"1","key":"1_CR10","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1109\/MCOMSTD.001.2000046","volume":"5","author":"J Jeong","year":"2021","unstructured":"Jeong, J., et al.: Mobility prediction for 5G core networks. IEEE Commun. Stand. Mag. 5(1), 56\u201361 (2021). https:\/\/doi.org\/10.1109\/MCOMSTD.001.2000046","journal-title":"IEEE Commun. Stand. Mag."},{"key":"1_CR11","doi-asserted-by":"publisher","unstructured":"Guo, P., Xiao, K., Ye, Z., Zhu, W.: Route optimization via environment-aware deep network and reinforcement learning. ACM Trans. Intell. Syst. Technol. 12(6) (2021). https:\/\/doi.org\/10.1145\/3461645","DOI":"10.1145\/3461645"},{"issue":"4","key":"1_CR12","doi-asserted-by":"publisher","first-page":"278","DOI":"10.2478\/mgr-2021-0020","volume":"29","author":"M \u0160auer","year":"2021","unstructured":"\u0160auer, M., Vystoupil, J., Novotn\u00e1, M., Widawski, K.: Central European tourist flows: intraregional patterns and their implications. Morav. Geogr. Rep. 29(4), 278\u2013291 (2021). https:\/\/doi.org\/10.2478\/mgr-2021-0020","journal-title":"Morav. Geogr. Rep."},{"key":"1_CR13","doi-asserted-by":"publisher","unstructured":"Lao, X., Deng, X., Gu, H., Yang, J., Yu, H., Xu, Z.: Comparing intercity mobility patterns among different holidays in china: a big data analysis. Appl. Spat. Anal. Policy (2022). https:\/\/doi.org\/10.1007\/s12061-021-09433-z","DOI":"10.1007\/s12061-021-09433-z"},{"key":"1_CR14","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.is.2018.02.004","volume":"75","author":"X Li","year":"2018","unstructured":"Li, X., et al.: Position prediction system based on spatio-temporal regularity of object mobility. Inf. Syst. 75, 43\u201355 (2018). https:\/\/doi.org\/10.1016\/j.is.2018.02.004","journal-title":"Inf. Syst."},{"key":"1_CR15","doi-asserted-by":"publisher","unstructured":"T\u00fcrk, U., \u00d6sth, J., Kourtit, K., Nijkamp, P.: The path of least resistance explaining tourist mobility patterns in destination areas using Airbnb data. J. Transp. Geogr. 94 (2021). https:\/\/doi.org\/10.1016\/j.jtrangeo.2021.103130","DOI":"10.1016\/j.jtrangeo.2021.103130"},{"key":"1_CR16","unstructured":"Data Science Process Alliance. https:\/\/www.datascience-pm.com\/crisp-dm-2. Accessed 24 July 2022"},{"key":"1_CR17","unstructured":"GSM Association Homepage. https:\/\/www.gsma.com\/mobileeconomy\/europe\/. Accessed 20 Dec 2022"},{"key":"1_CR18","unstructured":"ANACOM Homepage. https:\/\/www.anacom.pt\/streaming\/ServicosMoveis1T22.pdf?contentId=1722575&field=ATTACHED_FILE. Accessed 20 Dec 2022"}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Intelligent Transport Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-30855-0_1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,27]],"date-time":"2023-04-27T10:05:22Z","timestamp":1682589922000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-30855-0_1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031308543","9783031308550"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-30855-0_1","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"28 April 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"INTSYS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Transport Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lisbon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 December 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"intsys2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/futuretransport.eai-conferences.org\/2022\/","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":"Confy plus","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"45","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":"15","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":"33% - 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":"3.2","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":"2.2","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":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}