Modeling Individual and Team Behavior through Spatio-temporal Analysis
| Autor: | Erica Kleinman, Magy Seif El-Nasr, Sabbir Ahmad, Andy Bryant, Truong-Huy D. Nguyen, Zhaoqing Teng |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Interface (Java) business.industry Computer science 05 social sciences Spatio-Temporal Analysis Computer Science - Human-Computer Interaction ComputingMilieux_PERSONALCOMPUTING 020207 software engineering 02 engineering and technology Human-Computer Interaction (cs.HC) Visualization Knowledge extraction Human–computer interaction Analytics 0202 electrical engineering electronic engineering information engineering Human-in-the-loop 0501 psychology and cognitive sciences Cluster analysis business 050107 human factors Abstraction (linguistics) |
| Zdroj: | CHI PLAY |
| DOI: | 10.1145/3311350.3347188 |
| Popis: | Modeling players' behaviors in games has gained increased momentum in the past few years. This area of research has wide applications, including modeling learners and understanding player strategies, to mention a few. In this paper, we present a new methodology, called Interactive Behavior Analytics (IBA), comprised of two visualization systems, a labeling mechanism, and abstraction algorithms that use Dynamic Time Wrapping and clustering algorithms. The methodology is packaged in a seamless interface to facilitate knowledge discovery from game data. We demonstrate the use of this methodology with data from two multiplayer team-based games: BoomTown, a game developed by Gallup, and DotA 2. The results of this work show the effectiveness of this method in modeling, and developing human-interpretable models of team and individual behavior. |
| Databáze: | OpenAIRE |
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