with during the event, ranked by the measured strengths of the interactions. On top of that, the system provides an interactive web-based visualization that allows users to browse their ego networks across all supported systems, exploring the interplay of face-to-face time, on-line friendships and shared interest. The system also provides simple forms of recommendation, by suggesting the closure of social triangles that span the supported networks: for example, if attendee A has spent face-to-face time with attendee B, the system can point her to the profile of a third attendee C who is a Facebook friend of both A and B, and hasn’t met A yet at the event.
M. Atzmueller, L. Thiele, G. Stumme, and S. Kauffeld. Proc. Annual Machine Learning Conference of the Benelux (Benelearn 2017), Eindhoven, The Netherlands, Eindhoven University of Technology, (2017)
M. Atzmueller, A. Ernst, F. Krebs, C. Scholz, and G. Stumme. Postproceedings of the International Workshops MUSE & SenseML 2014, Nancy, France, and MSM 2014, Seoul, Korea, Springer Verlag, Heidelberg, Germany, (2016)
C. Scholz, J. Illig, M. Atzmueller, and G. Stumme. 25th ACM Conference on Hypertext and Social Media (to appear), Santiago, Chile, September 1-4, ACM, (2014)
C. Scholz, M. Atzmueller, and G. Stumme. Proc. Fourth ASE/IEEE International Conference on Social Computing (SocialCom), Boston, MA, USA, IEEE Computer Society, (2012)
B. Macek, C. Scholz, M. Atzmueller, and G. Stumme. 23rd ACM Conference on Hypertext and Social Media, HT '12, page 245-254. Milwaukee, WI, USA, June 25-28, 2012, ACM, (2012)Best Paper.