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.
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Thawonmas, R., Kurashige, M., Iizuka, K., Kantardzic, M. (2006). Clustering of Online Game Users Based on Their Trails Using Self-organizing Map. In: Harper, R., Rauterberg, M., Combetto, M. (eds) Entertainment Computing - ICEC 2006. ICEC 2006. Lecture Notes in Computer Science, vol 4161. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11872320_51
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DOI: https://doi.org/10.1007/11872320_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-45259-1
Online ISBN: 978-3-540-45261-4
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