V torek, 24. aprila 2014 ob 12.15 bo v PR-08 potekal 62. seminar FRI. Tokrat bo vabljeni gost dr. Miklós Krész iz univerze v Szegedu, Madžarska.
During the last decade social network analysis and mining became a key research area. Apart from the obvious applications in on-line social network services, the field plays central role in many classical business intelligence tasks such as customer attrition, risk analysis and campaign management. In order to capture the characteristics of the above problems, the dynamics of the corresponding network processes and network structural changes need to be studied. In this talk we will consider two relevant problems. Dynamic community detection is an algorithmic tool for the analysis of the lifetime of communities in real graphs. The study of infection processes in networks pose several algorithmic and modelling questions such as maximizing the spread of influence or approximating the real infection values. In addition to review applied models and methods, in the talk real-life applications will be also presented.
Miklós Krész is an associate professor at the Department of Applied Informatics, University of Szeged, Hungary. His main research interests are graph-based data mining and scheduling algorithms. In addition to studying theoretical aspects of the above topics, Miklós Krész is also working on industrially motivated application-oriented solutions. During the last years he coordinated several industrial R&D projects with leading Hungarian companies, such as Hungarian Telekom, OTP Bank or the Regional Transportation Center (Dél-Alföld).
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