Abstract
In this paper, user personalized services through the emotion perception required to support location-based sensing data preprocessing techniques and emotion data preprocessing techniques is studied for user's emotion data building and preprocessing in V-A emotion model. For this purpose the granular context tree and string matching based emotion pattern matching techniques are used. In addition, context-aware and personalized recommendation services technique using probabilistic reasoning is studied for personalized services based on context awareness.
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