Healthcare-event driven semantic knowledge extraction with hybrid data repository
AffiliationUniversity of Bedfordshire
Subjectsapplication program interfaces
NoSQL knowledge bases
data integration process
healthcare-event driven semantic knowledge extraction
hybrid data repository
ontological knowledge extraction
personalised health conditions
public data service API
semantic triple repository
social media Web API
knowledge based systems
resource description framework
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AbstractIn this paper, we introduce a Healthcare-Event (H-event) based knowledge extraction approach on a hybrid data repository. The repository collects (with individual user's permission) dynamic and large volume healthcare related data from various resources such as wearable sensors, social media Web APIs and our application itself. The proposed extraction approach relies on two data processing processes. One is the data integration process to dynamically retrieving the large data using public data service APIs. The first process also generates a set of big knowledge bases and stored in NoSQL storage. This paper will focus on the second extraction process that is the H-Event based ontological knowledge extraction for detecting and monitoring user's healthcare related situations, such as medical symptoms, treatments, conditions and daily activities from the NoSQL knowledge bases. The second process can be seen as post-processing step to detect more explicit healthcare knowledge about personalised health conditions and represent the knowledge using RDF formats in a semantic triple repository to enhance further data analytics.
CitationH Q Yu, X Zhao, X Zhen, F Dong, E Liu, G J Clapworthy, (2014) 'Healthcare-event driven semantic knowledge extraction with hybrid data repository'. 4th International Conference on Innovative Computing Technology (INTECH 2014), University of Bedfordshire, Luton 13-15 August.
TypeConference papers, meetings and proceedings
SponsorsThis work is supported in part by the European Commission under Grant FP7-ICT-9-5.2-VPH-600929 within the MyHealthAvatar project.
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