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Healthcare-event driven semantic knowledge extraction with hybrid data repository

  • Hong Qing Yu
    ,
  • Xia Zhao
    ,
  • Xin Zhen
    ,
  • Feng Dong
    ,
  • Enjie Liu
    ,
  • Gordon Clapworthy
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

In 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.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Publication milestones

  • Published - 20/10/2014

Publication status

Published - 20/10/2014

Publisher

Institute of Electrical and Electronics Engineers Inc., United States

ISBN (Electronic)

9781479942336

External Publication IDs

  • handle.net: 10547/338510
  • Scopus: 84925257601

Host publication title

Fourth edition of the International Conference on the Innovative Computing Technology (INTECH 2014)

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