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- W2234620583 abstract "This paper presents novel incremental statistical methods to analyze human daily activity patterns and to infer user intention. When context-aware systems provide the services to users, the system should resolve conflicts among applications as well as among users. In order to resolve these conflicts, we extracted daily activity patterns using incremental statistical methods. Generally, most people take the simultaneous activities at one time and want to be provided personalized services based on their own activity patterns. In this paper, we analyzed daily activity collected from physical sensors and devices and developed the incremental statistical method to determine simultaneous activities between the extracted activities. In addition, we organized the activities happened simultaneously into a set and analyzed temporal relation between sets to infer user intentions. We have experimented on a test-bed called USS (Ubiquitous Smart Space) for monitoring daily activity patterns and predicting user intention." @default.
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- W2234620583 date "2009-02-01" @default.
- W2234620583 modified "2023-09-27" @default.
- W2234620583 title "Incremental Statistical Methods for Activity Daily Pattern Extraction and User Intention Inference" @default.
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