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In recent years, there has been explosive growth in the amount of biomedical publications. In this paper, we propose a semantic framework that aims to automatically generate an ontology by extracting assertions and topics from multiple free-text scientific publications in PubMed. The pipeline approach for knowledge discovery and ontology generation in the proposed framework has been implemented on...
Understanding contextual information composed of both text and images is very useful for multimedia information processing. However, capturing such contexts is not trivial, especially while dealing with real datasets. Existing solutions such as using ontologies (e.g., WordNet) are mainly interested in individual terms, but they do not support identifying a group of terms that describe a specific context...
The ability to process, analyze, and evaluate realtime data and to identify their anomaly patterns is in response to realized increasing demands in various networking domains, such as corporations or academic networks. The challenge of developing a scalable, fault-tolerant and resilient monitoring system that can handle data in real-time and at a massive scale is nontrivial. We present a novel framework...
The growing affordability of smart phones and mobile devices has only added to this trend by encouraging prolonged durations of inactivity. In this paper, we present a middleware, called the Pervasive Middleware for Activity Recognition (PEMAR) that aims to increase the level of physical activity by creating a middleware for active games on mobile devices. For the PEMAR application, we present a human...
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