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User-defined preferences in a natural style is useful in the pervasive computing environment, but bring a great challenge to understand. People often express conditional as well as independent preferences. We propose an ontology-based quantitative model for conditional preferences that aims to enhance the inference capacity of conditional preference statements and thus reduce users' workload. Different...
Due to the rapid development of motion capture technology, more and more human motion databases appear. In order to effectively and efficiently manage human motion database, human motion classification is necessary. In this paper, we propose an ensemble based human motion classification approach (EHMCA). Specifically, EHMCA first extracts the descriptors from human motion sequences. Then, singular...
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