Ontology driven personal health knowledge discovery

被引:0
|
作者
Department of Computer Science, University of Bedfordshir, Luton, United Kingdom [1 ]
机构
来源
Lect. Notes Bus. Inf. Process. | / 649-663期
关键词
Activity tracking - Integration architecture - Knowledge discovery framework - Knowledge ontology - Management applications - Mobile applications - Parallel semantics - Smart sensor devices;
D O I
10.1007/978-3-319-21009-4_48
中图分类号
学科分类号
摘要
With fast development of smart sensor devices and mobile applications, all different kinds of information related to humans can be founded on the Internet that can be seen as a universal data repository or called Web of Data. Health or healthcare related data are not exceptional in the Web of Data age. The most important and valuable data comes from IoT such as sensors and mobile activity tracking applications to support developing self-health risk detection and management applications. This paper presents a comprehensive ontology driven knowledge discovery framework in personal health domain, which aims to reason and discover health knowledge from various data sources of IoT. The framework contains a sensor oriented Personal Wellness Knowledge Ontology and data integration architecture to complete a whole lifecycle of health knowledge detecting and reasoning path. In addition, a cloud computing based parallel semantic lifting algorithm is described for illustrating the semantic data generation process in detail. © Springer International Publishing Switzerland 2015.
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