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Automatic player behavior analysis system using trajectory data in a massive multiplayer online game

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Abstract

This paper presents a new automated behavior analysis system using a trajectory clustering method for massive multiplayer online games (MMOGs). The description of a player’s behavior is useful information in MMOG development, but the monitoring and evaluation cost of player behavior is expensive. In this paper, we suggest an automated behavior analysis system using simple trajectory data with few monitoring and evaluation costs. We used hierarchical classification first, then applied an extended density based clustering algorithm for behavior analysis. We show the usefulness of our system using trajectory data from the commercial MMOG World of Warcraft (WOW). The results show that the proposed system can analyze player behavior and automatically generate insights on players’ experience from simple trajectory data.

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Acknowledgement

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (No. 2011-0017595).

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Correspondence to Chang-Hun Kim.

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Kang, SJ., Kim, Y.B., Park, T. et al. Automatic player behavior analysis system using trajectory data in a massive multiplayer online game. Multimed Tools Appl 66, 383–404 (2013). https://doi.org/10.1007/s11042-012-1052-x

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