Health Insurance Data Processing using Linked Data
Vishal Shah1, Shridevi S2
1Vishal Shah, SCSE, Vellore Institute of Technology, Chennai, India.
2Dr. Shridevi S, SCSE, Vellore Institute of Technology, Chennai, India.
Manuscript received on 03 July 2019 | Revised Manuscript received on 07 July 2019 | Manuscript published on 30 August 2019 | PP: 864-869 | Volume-8 Issue-10, August 2019 | Retrieval Number: J90430881019/2019©BEIESP | DOI: 10.35940/ijitee.J9043.0881019
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The data in the organization is distributed among multiple structured databases. The large database makes the process of risk analysis difficult, as data is distributed in the organization. Information gathering for Risk analysis is more subjective and therefore, processing incomplete information over distributed databases increase more fault in risk analysis. Linked Data representation helps to make structured, distributed data more related, combined and ready to be processed. Linked Data approach makes data interlinked and semantically rich, extracting meaning with the use of machines and eliminating the human subjectivity factor in assessing insurance risk. Using Linked data, information retrieval process can be easier as data or databases interlinked semantically. The proposed technique uses a linked data approach for risk analysis and related information retrieval methods over structured data. The work efficiency is also tested and found to be good.
Keywords: Linked Data Analysis, Semantic-web, Ontology, Information retrieval and Gathering.
Scope of the Article: Healthcare Informatics