Learning from our movements – A roadmap towards mobility data analytics
From raw location recordings to mobility patterns - how can we exploit on the ubiquitous GPS technology in order to get knowledge about our movement behavior? Which are the most representative examples of mobility patterns that can be mined from humans’ mobility datasets? In this talk, issues and solutions on Mobility Data Analytics (MDA) are overviewed, including data acquisition, processing, and mining aspects. Current trends in MDA, such as semantic / holistic trajectory modelling and big mobility data management, are also presented. Use cases include land, sea, and air space movement.
Dr. Yannis Theodoridis is Professor of Data Science at the Department of Informatics, University of Piraeus, Greece. He serves or has served at the editorial boards of ACM Computing Surveys (2016-) and the Int'l Journal on Data Warehousing and Mining (2005-), as lifelong member of the Symposium on Spatial and Temporal Databases - SSTD endowment (2010-), general co-chair for SSTD’03 and ECML/PKDD'11, PC vice-chair for IEEE ICDM'08, and PC member for several conferences, including SIGMOD / PODS, ICDE, KDD, ICDM, etc. He has delivered invited talks and seminars in the area of Mobility Data Analytics, included an invited course during 2018 ACM Europe Summer School on Data Science. He has participated in a number of research projects related to Data Science and Big Data, with EU Horizon 2020 funded MASTER (2018-21), Track-and-Know (2018-20), and datAcron (2016-18) being the most recent ones. He has co-authored three monographs and more than 100 refereed articles in scientific journals and conferences with over 10,000 citations so far, according to Google Scholar. He holds a Dipl. Eng. (1990) and Ph.D. (1996) in Computer Engineering, both from the National Technical University of Athens (NTUA). Personal homepage: www.unipi.gr/faculty/ytheod/.
AIT Austrian Institute of Technology GmbH
June 6th, 2019, 15:00 – 16:00
Giefinggasse 2, 1210 Vienna