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
MetadataShow full item record
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.
Showing items related by title, author, creator and subject.
Enhancing learner knowledge and the application of that knowledge via computer based assessmentReynolds, Lynne; University of Bedfordshire (University of Bedfordshire, 2013-02)This paper details the process that the author went through as a novice action researcher whilst designing and implementing a new computer based assignment within a Higher Education institution within the UK. The paper outlines the initial stages of a project which was designed to assist students in the transformation from declarative to functioning knowledge (Biggs & Tang 2011). The implementation of a new summative assessment was to help students to develop a deeper rather than surface approach to learning. Owing to the personal and professional beliefs of the author, the project was designed using Norton's (2009) action research methodology of ITDEM. The research also consisted of a specific theoretical framework which included Kolb's (1984) and Atherton's (2009) theories on experiential learning and a constructivist approach (Swan 2005) to developing and designing an intervention. It also highlights the difficulties that were faced by the researcher whilst identifying and tackling this issue and implementing the new assessment. In addition during the initial stages, the research design encompassed the piloting of the Touchstone Open Source Platform because the University's Question Mark Platform was not compatible with the demands of the new assignment. This would allow an online assignment to be utilised. It would also produce instant results and feedback for the students whilst reducing marking loads (Wilkinson & Rai 2007). In order to evaluate and analyse the results from the research, data was collected and measured through the attainment of individual summative grades which were available as part of the normal academic process. Moreover, the grades that would normally be available within the university infrastructure for grading purposes were utilised to collect data on the new assessment. Upon analysis, initial results indicated an increase in the number of students who had achieved a level of functioning knowledge in comparison to previous cohorts (see fig 1). However, despite some indications of success, the author is unable to generalise this success at present owing to this project being a pilot study for the new Question Mark Platform. This paper concludes with a number of suggestions for modifying the new assessment and recommendations for the next cycle in the research process.