• Journal of Korea Game Society
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• v.15 no.4
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• pp.59-68
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• 2015

The progress in Information & Communication Technology enables data scientists to analyze big data for identifying peoples' daily lives and tacit preferences. A variety of industries already aware the potential usefulness of analyzing big data. However limited use of big data has been performed in game industry. In this research, we adopt data mining technique to analyze data gathered from a strategic simulation game. Decision Tree, Random Forest, Multi-class SVM, and Linear Regression techniques are used to find the most important variables to users' game levels. We provide practical guides for game design and usability based on the analyzed results.

• IE interfaces
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• v.16 no.2
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• pp.258-267
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• 2003

Recently, virtual reality technologies have been rapidly developed and realtime virtual simulation methods have been extensively employed for several application areas such as game, sports, manufacturing, military, and so on. A 3D database in realtime virtual simulation plays a key role because it makes users feel reality in virtual space. In a application view of 3D database, a systematic construction approach is required to reduce its construction time and increase its quality. However, many researches have been mostly focused on realtime graphic issues and its key technologies. In virtual simulation of transportation equipments, this paper proposes a systematic construction process of 3D database consisting of four stages as follows: 1) determine the activity space of a equipment, 2) collect data related to 3D database construction, 3) make a 3-dimensional modeling strategy, and 4) generate and evaluate a 3D model. This paper also introduces a new procedure of 3D environment modeling, which summarizes and expands our modeling experiences, to be used as a modeling guide.