Clustering of Online Game Users Based on Their Trails Using Self-organizing Map

Ruck Thawonmas, Masayoshi Kurashige, Keita Iizuka, Mehmed M. Kantardzic

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.