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With the advent of the Internet of things (IoT) and smart sensor technologies, the data-driven paradigm has been found promising to support human behavioral analysis in a smart home for better healthcare and well-being of senior adults. This work focuses on discovering daily activity routines from sensor data collected in a smart home. By representing the sensor data as a matrix, daily activity routines...
With the advent of ubiquitous computing and sensor technologies, indoor trajectory data of individuals can readily be collected to support analysis of their underlying movement behaviors. Different methods for activity recognition have been proposed where supervised learning algorithms are often adopted. In many applications like elderly care, the behaviors to be characterized are often not known...
Recent findings show that online reviews, blogs, and discussion forums on chronic diseases and drugs are becoming important supporting resources for patients. Extracting information from these substantial bodies of texts is useful and challenging. We developed a generative probabilistic aspect mining model (PAMM) for identifying the aspects/topics relating to class labels or categorical meta-information...
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