Dynamics of complex systems
Visualizing Competitive Behaviors in Multi-User Virtual Environments
VIS '04 Proceedings of the conference on Visualization '04
Mining Frequent Spatio-Temporal Sequential Patterns
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Clustering of online game users based on their trails using self-organizing map
ICEC'06 Proceedings of the 5th international conference on Entertainment Computing
ICEC'05 Proceedings of the 4th international conference on Entertainment Computing
High-level visualization of users' navigation in virtual environments
INTERACT'05 Proceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction
Visualization of online-game players based on their action behaviors
International Journal of Computer Games Technology - Networking for Computer Games
Automatic player behavior analysis system using trajectory data in a massive multiplayer online game
Multimedia Tools and Applications
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To keep online games interesting to their players, it is important to detect players' behaviors. In this paper, in order to understand players' movement in online games, we propose a method for extraction of players' paths from their trails. In the proposed method, locations in a given map that are frequently visited are first intensified by cellular automata, and paths are then derived by the Hilditch thinning algorithm. Players' trails from an experimental online game, where three typical game missions are available, are used for performance evaluation. For performance evaluation, the proposed method is compared with a method using the median filter and the Hilditch thinning algorithm, a typical recipe in the area of image processing. According to the comparison results, the proposed method significantly outperforms its counter part in all cases, except the case with limited movement patterns.