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Big Data and Big Water: Mining Ocean Vessel Trajectory Data
In this presentation we will focus on the ongoing work in exploration and analysis of data from ocean vessel movements, using the Automatic Identification System (AIS) data. We will discuss some of the challenges and benefits related to the large-scale exploration and analysis of AIS data. We will look at detection of anomalous trajectories of ships in mid-ocean and in port vicinity, and at the ecologically-oriented detection and analysis of data related to fishing activities. We will discuss our early results in these select applications, including data representation and data modeling techniques, particularly the clustering techniques, classification, and attribute engineering used in our work. We will round up with discussion of potential future work with AIS data.
About The Speaker:
Stan Matwin is a Professor and Canada Research Chair in the Faculty of Computer Science at Dalhousie University, where he directs the Institute for Big Data Analytics. He is also a Professor at the Institute of Computer Science, Polish Academy of Sciences. His research interests are in text analytics, data mining, as well as in data privacy. Author and co-author of more than 250 research papers and articles, Stan is a former President of the Canadian Artificial Intelligence Society, a member of the Scientific Council of the Polish Artificial Intelligence Society, and a member of Association Francaise pour l’Intelligence Artificielle.