The MODAP-Workshop on "Mobile Analytics Meets Social Media" is organized by the Knowledge Discovery Department (KD) at the Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS) in Sankt Augustin, Germany.
The Fraunhofer-Gesellschaft is Germany’s leading organization of research institutions for applied research. The Knowledge Discovery Department at Fraunhofer IAIS, headed by Dr. Michael May, is a research group (50 scientists and engineers) located in the field of Machine Learning and Data Mining.
The department has both applied and theoretically oriented research groups. On the theoretical side, it focuses on topics such as graph mining, statistical relational learning, and visual analytics. Much of this work is done in co-operation with the University of Bonn, where Prof. Stefan Wrobel, the director of IAIS, holds the chair for Intelligent Analysis and Information Systems. On the applied side, KD does applications in spatial & mobility mining, text & opinion mining, fraud detection, and distributed data mining. Many of the projects are directly funded by industry. One such project on mobility mining using GPS data for outdoor advertising received the "Best Study Award" from the German Association for Market Research in 2008.
In the past 10 years KD has coordinated a number European Research Networks: the Knowledge Discovery Network of Excellence KDNet (2001-2004) and the Knowledge Discovery in Ubiquitous Environments Coordination Action (2005-2008), both FET-Open. KD contributed to the GeoPKDD project and is active in the management board of MODAP. Starting in 2010 KD is working on the three year FET-Open project LIFT (Local Inference in Massively Distributed Systems), which deals with data mining and monitoring in very large sensor & traffic networks (taking care of privacy constraints). Since 2011 KD is furthermore part of the project DATASIM which aims to provide a new and highly detailed spatio-temporal microsimulation methodology for human mobility, grounded on massive amounts of Big data.