The Complexity of Approximating a Trembling Hand Perfect Equilibrium of a Multi-player Game in Strategic Form

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Mining user behavior patterns in social networks is of great importance in user behavior analysis, targeted marketing, churn prediction and other applications. However, less effort has been made to study the evolution of user behavior in social communities. In particular, users join and leave communities over time. How to automatically detect the online community transitions of individual users is a research problem of immense practical value yet with great technical challenges. In this paper, we propose an algorithm based on the Minimum Description Length (MDL) principle to trace the evolution of community transition of individual users, adaptive to the noisy behavior. Experiments on real data sets demonstrate the efficiency and effectiveness of our proposed method.
Original languageEnglish
Title of host publicationAlgorithmic Game Theory : 7th International Symposium, SAGT 2014, Haifa, Israel, September 30 – October 2, 2014. Proceedings
EditorsRon Lavi
Number of pages13
PublisherSpringer VS
Publication yearJun 2014
ISBN (print)978-3-662-44802-1
ISBN (Electronic)978-3-662-44803-8
Publication statusPublished - Jun 2014
EventSymposium on Algorithmic Game Theory - Haifa, Israel
Duration: 30 Sep 20142 Oct 2014
Conference number: 7


ConferenceSymposium on Algorithmic Game Theory
SeriesLecture Notes in Computer Science

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ID: 81805139