{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:51:12Z","timestamp":1760241072861,"version":"build-2065373602"},"publisher-location":"Basel Switzerland","reference-count":22,"publisher":"MDPI","license":[{"start":{"date-parts":[[2019,11,20]],"date-time":"2019-11-20T00:00:00Z","timestamp":1574208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"DOI":"10.3390\/proceedings2019031025","type":"proceedings-article","created":{"date-parts":[[2019,11,20]],"date-time":"2019-11-20T11:06:03Z","timestamp":1574247963000},"page":"25","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Data Framework for Road-Based Mass Transit Systems Data Mining Project"],"prefix":"10.3390","author":[{"given":"Teresa","family":"Crist\u00f3bal","sequence":"first","affiliation":[{"name":"Institute for Cybernetics, University of Las Palmas de Gran Canaria, Campus de Tafira, 35017 Las Palmas, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabino","family":"Padr\u00f3n","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8313-5124","authenticated-orcid":false,"given":"Alexis","family":"Quesada-Arencibia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francisco","family":"Alay\u00f3n","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1433-3730","authenticated-orcid":false,"given":"Carmelo R.","family":"Garc\u00eda","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1624","DOI":"10.1109\/TITS.2011.2158001","article-title":"Data-Driven Intelligent Transportation Systems: A Survey","volume":"12","author":"Zhang","year":"2011","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_2","first-page":"674","article-title":"Advanced public transport and intelligent transport systems: New modelling challenges","volume":"12","author":"Nuzzolo","year":"2016","journal-title":"Transp. A Transp. Sci."},{"key":"ref_3","first-page":"13","article-title":"The CRISP-DM Model: The New Blueprint for Data Mining","volume":"5","author":"Shearer","year":"2000","journal-title":"J. Data Wareh."},{"key":"ref_4","unstructured":"Gray, J. (2005). Input: Concepts, instances, and attributes. Data Mining. Practical Machine Learning Tools and Techniques, Morgan Kaufmann Publishers. [2nd ed.]."},{"key":"ref_5","unstructured":"Agard, B., Morency, C., and Tr\u00e9panier, M. (2005, January 17\u201319). Mining public transport user behaviour from smart card data. Proceedings of the 12th IFAC Symposium on Information Control Problems in Manufacturing, St-Etienne, France."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Lathia, N., Froehlich, J., and Capra, L. (2010, January 13\u201317). Mining public transport usage for personalised intelligent transport systems. In Proceeding of the 2010 IEEE International Conference Data Mining, Sydney, Australia.","DOI":"10.1109\/ICDM.2010.46"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1016\/j.pmcj.2012.10.007","article-title":"Individuals among commuters: Building personalised transport information services from fare collection systems","volume":"9","author":"Lathia","year":"2013","journal-title":"Pervasive Mob. Comput."},{"key":"ref_8","first-page":"682390","article-title":"Short-Term Bus Passenger Demand Prediction Based on Time Series Model and Interactive Multiple Model Approach","volume":"526","author":"Xue","year":"2015","journal-title":"Discrete Dyn. Nat. Soc."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Celebi, D., Bolat, B., and Bayraktar, D. (2009, January 6\u20139). Light Rail Passenger Demand Forecasting by Artificial Neural Networks. In Proceeding of the 2009 International Conference on Computers & Industrial Engineering, Troyes, France.","DOI":"10.1109\/ICCIE.2009.5223851"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"3135","DOI":"10.1109\/TITS.2017.2679179","article-title":"Spatio-Temporal Analysis of Passenger Travel Patterns in Massive Smart Card Data","volume":"18","author":"Zhao","year":"2017","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1016\/j.trc.2015.09.016","article-title":"Time of day intervals partition for bus schedule using GPS data","volume":"60","author":"Bie","year":"2015","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_12","first-page":"1042","article-title":"A Methodology for Denoising and Generating Bus Infrastructure Data","volume":"16","author":"Pinelli","year":"2015","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"84","DOI":"10.1016\/j.tra.2015.03.012","article-title":"Rethinking bus punctuality by integrating Automatic Vehicle Location data and passenger patterns","volume":"75","author":"Barabino","year":"2015","journal-title":"Transp. Res. Part A Policy Pract."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.1016\/j.trpro.2017.12.116","article-title":"Identifying Irregularity Sources by Automated Location Vehicle Data","volume":"27","author":"Mozzoni","year":"2017","journal-title":"Transp. Res. Procedia"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.ins.2014.09.005","article-title":"Validating the coverage of bus schedules: A Machine Learning approach","volume":"293","author":"Gama","year":"2015","journal-title":"Inf. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"45","DOI":"10.5038\/2375-0901.17.2.3","article-title":"Artificial Neural Network Travel Time Prediction Model for Buses Using Only GPS Data","volume":"17","author":"Gurmu","year":"2007","journal-title":"J. Public Transp."},{"key":"ref_17","first-page":"151","article-title":"Bus Arrival Time Prediction Using Support Vector Machines","volume":"10","author":"Yu","year":"2007","journal-title":"J. Intell. Transp. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1080\/18128600902929591","article-title":"Dynamic multi-interval bus travel time prediction using bus transit data","volume":"6","author":"Chang","year":"2010","journal-title":"Transportmetrica"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Lee, W.-C., Si, W., Chen, L.-J., and Chen, M.-C. (2012, January 6\u20139). HTTP: A new framework for bus travel time prediction based on historical trajectories. In Proceeding of the 20th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, Redondo Beach, CA, USA.","DOI":"10.1145\/2424321.2424357"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1061\/(ASCE)TE.1943-5436.0000312","article-title":"Bus-Arrival-Time Prediction Models: Link-Based and Section-Based","volume":"138","author":"Chen","year":"2012","journal-title":"J. Transp. Eng."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1049\/iet-its:20080013","article-title":"Travel time prediction under heterogeneous traffic conditions using global positioning system data from buses","volume":"3","author":"Vanajakshi","year":"2009","journal-title":"IET Intell. Transp. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Crist\u00f3bal, T., Padr\u00f3n, G., Quesada-Arencibia, A., Alay\u00f3n, F., de Blasio, G., and Garc\u00eda, C. (2019). Bus Travel Time Prediction Model Based on Profile Similarity. Sensors, 19.","DOI":"10.3390\/s19132869"}],"event":{"name":"The International Conference on Ubiquitous Computing and Ambient \u202aIntelligence","acronym":"UCAmI 2019"},"container-title":["13th International Conference on Ubiquitous Computing and Ambient \u202aIntelligence UCAmI 2019\u202c"],"original-title":[],"link":[{"URL":"https:\/\/www.mdpi.com\/2504-3900\/31\/1\/25\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:35:51Z","timestamp":1760189751000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2504-3900\/31\/1\/25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,20]]},"references-count":22,"alternative-id":["proceedings2019031025"],"URL":"https:\/\/doi.org\/10.3390\/proceedings2019031025","relation":{},"subject":[],"published":{"date-parts":[[2019,11,20]]}}}