A prediction and auto-execution system of smartphone application services based on user context-awareness |
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| Affiliation: | 1. Ubiquitous Convergence Research Institute, Ajou University, Paldal Hall 408, San 5, Woncheon-dong, Yeongtong-gu, Suwon 443-749, Republic of Korea;2. Software R&D Center in Samsung Electronics Device Solutions Department, 95, Samsung 2-ro, Giheung-gu, Yongin-si, Gyeonggi-do 446-811, Republic of Korea;3. Department of Electrical and Computer Engineering, Ajou University, Woncheon Hall 305, San 5, Woncheon-dong, Yeongtong-gu, Suwon 443-749, Republic of Korea;1. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China;2. Department of Computer Science, Pace University, Manhattan NYC, NY 10038, USA;1. Department of Digital Information Engineering, Hankuk University of Foreign Studies, Republic of Korea;2. Department of Multimedia Engineering, Dongguk University, Republic of Korea;1. Telenor Research, Snarøyveien 30, N-1331, Fornebu, Norway;2. University of Cambridge, Computer Laboratory, 15 JJ Thomson Avenue, Cambridge, UK;1. Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan, ROC;2. Department of Electrical Engineering, National Ilan University, I-Lan, Taiwan, ROC;1. College of Computer Science, Chongqing University, Chongqing, China;2. Key Laboratory of Dependable Service Computing in Cyber Physical Society (Chongqing University), Ministry of Education, China;3. School of Electrical and Computer Engineering, Oklahoma State University, Stillwater, USA |
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| Abstract: | Smartphones have emerged as suitable environments for user context-awareness and intelligent service provision due to the high penetration rate, the high usability, various embedded sensors, and so on. In particular, its most unique characteristic is the usage of various applications. However, the most of existing studies through the three steps process (log collection, context inference, and service provision) did not consider smartphone applications (Apps) as the target service. Smartphone users still have to use Apps with manual controls by own decision. Therefore, in this paper, we propose a system to predict smartphone applications based on inferring user context. We define a mobile context model with a new level of context (Situation) and its inference method to perceive a user’s intention or purpose related to the App usage. Based on the Situation context, the system predicts Apps which can be useful and helpful for a user and automatically executes it on his/her smartphone. With the proposed system, it will be possible to autonomously provide and manage smartphone application services without users’ perception or intervention. |
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| Keywords: | Smartphone application (App) Context awareness Context inference Service prediction Intelligent App service |
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