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Publication search results
found 89 matches
- 2023
- Andrea Delgado, Daniel Calegari:
Process Mining for Improving Urban Mobility in Smart Cities: Challenges and Application with Open Data. HICSS 2023: 1716-1725 - 2022
- Yushan Jiang, Shuteng Niu, Kai Zhang, Bowen Chen, Chengtao Xu, Dahai Liu, Houbing Song:
Spatial-Temporal Graph Data Mining for IoT-Enabled Air Mobility Prediction. IEEE Internet Things J. 9(12): 9232-9240 (2022) - Francisco Neves, Anna Carolina Finamore, Sara C. Madeira, Rui Henriques:
Mining Actionable Patterns of Road Mobility From Heterogeneous Traffic Data Using Biclustering. IEEE Trans. Intell. Transp. Syst. 23(7): 6430-6445 (2022) - Javier J. Sánchez Medina, Juan Antonio Guerra-Montenegro, Agustín J. Sánchez-Medina, Itziar G. Alonso-González, David Sánchez-Rodríguez:
On Smart Mobility and Data Stream Mining. EUROCAST 2022: 378-383 - Michiel Dhont, Elena Tsiporkova, Nicolás González-Deleito:
Mining of Spatiotemporal Trajectory Profiles Derived from Mobility Data. ICDM (Workshops) 2022: 1-9 - Yaksh J. Haranwala, Salman Haidri, Terrence S. Tricco, Vinicius Prado da Fonseca, Amílcar Soares:
A Dashboard Tool for Mobility Data Mining Preprocessing Tasks. MDM 2022: 278-281 - Bettina Berendt, Stan Matwin, Chiara Renso, Fran Meissner, Francesca Pratesi, Alessandra Raffaetà, Geoffrey Rockwell:
Mobility Data Mining: from Technical to Ethical (Dagstuhl Seminar 22022). Dagstuhl Reports 12(1): 35-66 (2022) - 2021
- Shuangyan Wang, Gang Mei, Salvatore Cuomo:
A generic paradigm for mining human mobility patterns based on the GPS trajectory data using complex network analysis. Concurr. Comput. Pract. Exp. 33(4) (2021) - Philippe Büdinger, Tor-Morten Grønli:
Unsupervised data mining on spatial-temporal passenger mobility and survey data during Covid-19. IEEE BigData 2021: 4327-4332 - Mirco Nanni, Agnese Bonavita, Riccardo Guidotti:
City Indicators for Mobility Data Mining. EDBT/ICDT Workshops 2021 - Etienne Côme, Latifa Oukhellou, Allou Samé, Lijun Sun:
Machine learning and data mining for urban mobility intelligence. ESANN 2021 - 2020
- Omid Isfahani Alamdari:
Scalable Processing and Mining of Big Mobility Data. University of Pisa, Italy, 2020 - Shreya Ghosh, Soumya K. Ghosh, Rajkumar Buyya:
MARIO: A spatio-temporal data mining framework on Google Cloud to explore mobility dynamics from taxi trajectories. J. Netw. Comput. Appl. 164: 102692 (2020) - Francesco Zinnari, Silvia Carla Strada, Mara Tanelli, Simone Formentin, Gianluca Savaia, Sergio M. Savaresi:
Mining the electrification potential of fuel-based vehicles mobility patterns: a data-based approach. ICHMS 2020: 1-6 - Giacomo Cacciapaglia, Corentin Cot, Francesco Sannino:
Mining Google and Apple mobility data: Temporal Anatomy for COVID-19 Social Distancing. CoRR abs/2008.02117 (2020) - 2019
- Danya Bachir:
Estimating Urban Mobility with Mobile Network Geolocation Data Mining. (Estimation de la mobilité urbaine par l'exploitation des données de géolocalisation de téléphonie mobile). Telecom SudParis, Évry, Essonne, France, 2019 - Vinicius Monteiro de Lira:
Mining human mobility data and social media for smart ride sharing. University of Pisa, Italy, 2019 - Galina Deeva, Johannes De Smedt, Jochen De Weerdt, María Óskarsdóttir:
Mining Behavioural Patterns in Urban Mobility Sequences Using Foursquare Check-in Data from Tokyo. COMPLEX NETWORKS (2) 2019: 931-943 - Shingo Enami, Kohei Shiomoto:
Spatio-temporal human mobility prediction based on trajectory data mining for resource management in mobile communication networks. HPSR 2019: 1-6 - Vinicius Monteiro de Lira:
Mining Human Mobility Data and Social Media for Smart Ride Sharing. MDM 2019: 385-386 - Thiago Andrade, Brais Cancela, João Gama:
Mining Human Mobility Data to Discover Locations and Habits. PKDD/ECML Workshops (2) 2019: 390-401 - Thiago Andrade, Brais Cancela, João Gama:
Mining Human Mobility Data to Discover Locations and Habits. CoRR abs/1909.11406 (2019) - 2018
- Cristina Kadar, Irena Pletikosa:
Mining large-scale human mobility data for long-term crime prediction. EPJ Data Sci. 7(1): 26 (2018) - Mohamed Batran, Mariano Gregorio Mejia, Hiroshi Kanasugi, Yoshihide Sekimoto, Ryosuke Shibasaki:
Inferencing Human Spatiotemporal Mobility in Greater Maputo via Mobile Phone Big Data Mining. ISPRS Int. J. Geo Inf. 7(7): 259 (2018) - Roberto Pellungrini, Luca Pappalardo, Francesca Pratesi, Anna Monreale:
A Data Mining Approach to Assess Privacy Risk in Human Mobility Data. ACM Trans. Intell. Syst. Technol. 9(3): 31:1-31:27 (2018) - Roelant A. Stegmann, Indre Zliobaite, Tuukka Tolvanen, Jaakko Hollmén, Jesse Read:
A survey of evaluation methods for personal route and destination prediction from mobility traces. WIREs Data Mining Knowl. Discov. 8(2) (2018) - Mohamed Batran, Mariano Gregorio Mejia, Yoshihide Sekimoto, Ryosuke Shibasaki:
Inference of Human Spatiotemporal Mobility in Greater Maputo by Mobile Phone Big Data Mining. ATT@IJCAI 2018: 1-8 - Guangshuo Chen, Aline Carneiro Viana, Marco Fiore:
Takeaways in Large-scale Human Mobility Data Mining : (Invited Paper). LANMAN 2018: 55-60 - Mohamed Batran, Hiroshi Kanasugi, Takehiro Kashiyama, Yoshihide Sekimoto, Ryosuke Shibasaki:
Sensing Population Mobility through City Boundary in Greater Maputo via Mobile Phone Big Data Mining. SERVICES 2018: 9-10 - Giuseppe Lugano:
Assessing Individual and Group Behavior from Mobility Data: Technological Advances and Emerging Applications. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018
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