This survey reviews the state-of-the-art on the applicability of machine learning techniques for behavioral awareness. Not only is behavioral awareness an important capability of ambient assisted living environments to better support individuals during their activities of daily living, it is also gaining attention as a way to identify individuals based on distinguishing or unique features in their behavior. In this work, we not only pay attention to individual behavior but also to behavioral traits of a group of individuals as a whole. This survey documents a broad overview of the state-of-the-art in behavioral recognition, learning and mining. It provides an overview of how activities can be recognized through the identification and classification of certain features in event-based data streams. This overview highlights a variety of well-known probabilistic learning and prediction methods and how they have been applied for the purpose of identification and activity recognition.
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