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Community based multi-group activity prediction and member identification

机译:基于社区的多组活动预测和成员识别

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Background: Human activity recognition is a process by which a system can identify different human activities based on the observations on the individual's action and his/her surroundings. However, human beings are social by nature and like to build community depending upon a common point of interest and common characteristics. Therefore, for getting complete knowledge of an individual's activities, community based activity recognition - an extension of single activity recognition and group activity recognition is necessary. Additionally, for community activity monitoring, activity prediction is equi-important with activity recognition because early knowledge of the activities use to compare with the recognize activities for studying the certain change in the community activity pattern. We develop a recommendation system to identify the users based on their past and current performed activities. The system continuously identifies the users and generate alert to the user only if the system monitors any different activity pattern. The combination of the recommendation and alert system will as a whole monitor the individual's daily activity and track the irregularity in his/her life by comparing different activities over the time scale.
机译:背景:人类活动识别是一个过程,系统可以通过该过程基于对个人行为及其周围环境的观察来识别不同的人类活动。然而,人类天生就是社会的,喜欢根据共同的兴趣点和共同特征建立社区。因此,为了获得有关个人活动的完整知识,基于社区的活动识别-扩展单个活动识别和小组活动识别是必要的。此外,对于社区活动监控,活动预测与活动识别同等重要,因为活动的早期知识用于与识别活动进行比较,以研究社区活动模式的某些变化。我们开发了一个推荐系统,可以根据用户过去和当前进行的活动来识别他们。仅当系统监视任何不同的活动模式时,系统才会连续标识用户并向用户发出警报。推荐和警报系统的组合将整体上监视个人的日常活动,并通过比较时间范围内的不同活动来跟踪其生活中的不规律性。

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