Clustering of online game users based on their trails using self-organizing map

Authors:
Ruck Thawonmas;Masayoshi Kurashige;Keita Iizuka;Mehmed Kantardzic
Affiliations:
Intelligent Computer Entertainment Laboratory, Department of Human and Computer Intelligence, Ritsumeikan University, Kusatsu, Shiga, Japan;Intelligent Computer Entertainment Laboratory, Department of Human and Computer Intelligence, Ritsumeikan University, Kusatsu, Shiga, Japan;Intelligent Computer Entertainment Laboratory, Department of Human and Computer Intelligence, Ritsumeikan University, Kusatsu, Shiga, Japan;Data Mining Lab, Computer Engineering and Computer Science Department, University of Louisville, Louisville, KY
Venue:
ICEC'06 Proceedings of the 5th international conference on Entertainment Computing
Year:
2006

Citing 3
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Abstract

To keep an online game interesting to its users, it is important to know them. In this paper, in order to characterize user characteristics, we discuss clustering of online-game users based on their trails using Self Organization Map (SOM). As inputs to SOM, we introduce transition probabilities between landmarks in the targeted game map. An experiment is conducted confirming the effectiveness of the presented technique.