Game Theoretic Approaches to Knowledge Discovery and Data Mining

  • Y. Narahari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6118)


Game theory is replete with brilliant solution concepts such as the Nash equilibrium, the core, the Shapley value, etc. These solution concepts and their extensions are finding widespread use in solving several fundamental problems in knowledge discovery and data mining. The problems include clustering, classification, discovering influential nodes, social network analysis, etc. The first part of the talk will present the conceptual underpinnings underlying the use of game theoretic techniques in such problem solving. The second part of the talk will delve into two problems where we have recently obtained some interesting results: (a) Discovering influential nodes in social networks using the Shapley value, and (b) Identifying topologies of strategically formed social networks using a game theoretic approach.


Information System Social Network Artificial Intelligence Data Mining Nash Equilibrium 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Y. Narahari
    • 1
  1. 1.Indian Institute of ScienceBangaloreIndia

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