• Journal of Information Technology Applications and Management
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• v.28 no.6
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• pp.1-21
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• 2021

This study is about Augmented Reality Game (AR Game) applied to Pokemon Go, which has recently been a sensational game. We focused on and analyzed the intention for continuous use as a dependent variable. We made hypotheses through previous studies and used spatial presence, perceived interactivity, perceived pleasure, and sickness as independent variables. Immersion was set up as a mediating variable. We conducted the study using 198 data, which people who experienced AR games responded. The results were as follows. First, spatial presence and perceived pleasure were found to have a significant effect on immersion, as in previous studies. Second, the relationship between sickness and immersion, which were shown to have a negative relationship in previous studies, we found that variables had a positive relationship unlike previous studies and rejected the hypothesis. Third, perceived interactivity, which is one of the crucial variables to affect the intention for continuous use, we found not to have a significant relationship among perceived interactivity, immersion, and the intention for continuous use. This result is opposite from previous studies, and further research on this issue is expected. We conducted this study with an individual user's view on immersion and the intention for continuous use rather than focusing on technical or political topics. Besides, this study has a significance that drew different results from previous studies and explored people who relish AR games with the characteristics of personal variables.

• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.99-110
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• 2011

Mobile environments rapidly changing and digital convergence widely employed, mobile devices including smart phones have been playing a critical role that changes users' lifestyle in the areas of entertainments, businesses and information services. The various services using mobile devices are developing to meet the personal needs of users in the mobile environments. Especially, an LBS (Location-Based Service) is combined with other services and contents such as augmented reality, mobile SNS (Social Network Service), games, and searching, which can provide convenient and useful services to mobile users. In this paper, we design and implement the prototype of mobile personal assistant (PA) agents. Our personal assistant agent helps users do some tasks by hiding the complexity of difficult tasks, performing tasks on behalf of the users, and reflecting the preferences of users. To identify user's preferences and provide personalized services, clustering and classification algorithms of data mining are applied. The clusters of the log data using clustering algorithms are made by measuring the dissimilarity between two objects based on usage patterns. The classification algorithms produce user profiles within each cluster, which make it possible for PA agents to provide users with personalized services and contents. In the experiment, we measured the classification accuracy of user model clustered using clustering algorithms. It turned out that the classification accuracy using our method was increased by 17.42%, compared with that using other clustering algorithms.