Abstract
For thousands of years, people have been playing games of chance or wagering on the outcomes of various games and events. As a medium, the computer game is currently in a period of rapid development. From a design point of view, video games are becoming more complex and they are rapidly spreading to new platforms such as mobile phones, pocket computers, and websites. This paper aims to determine whether Association mining algorithm applied to an online social games database would provide the game designers with meaningful rules that would help improve the design of the game. A data set of online social gamer profile was created. The database contains various aspects of social games. The rules generated from association analysis would be of tremendous benefit to the gaming industry, as they can then use them to optimize game design features.
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Ansari, N., Talreja, M., Desai, V. (2013). Data Mining in Online Social Games. In: Kumar M., A., R., S., Kumar, T. (eds) Proceedings of International Conference on Advances in Computing. Advances in Intelligent Systems and Computing, vol 174. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0740-5_95
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DOI: https://doi.org/10.1007/978-81-322-0740-5_95
Publisher Name: Springer, New Delhi
Print ISBN: 978-81-322-0739-9
Online ISBN: 978-81-322-0740-5
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