Personalized Retrieval in the Medical Domain: A NoSQL Solution Based on Ontology Building

Ghada Besbes (), Sana Ben Abdallah Ben Lamine () and Hajer Baazaoui-Zghal ()
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Ghada Besbes: Riadi Laboratory, ENSI, University of Manouba, Tunisia
Sana Ben Abdallah Ben Lamine: Riadi Laboratory, ENSI, University of Manouba, Tunisia
Hajer Baazaoui-Zghal: ETIS UMR 8051, CY University, ENSEA, CNRS, Cergy F-95000, France

Journal of Information & Knowledge Management (JIKM), 2020, vol. 19, issue 04, 1-22

Abstract: Managing medical information in a Big Data context is a challenging task since searching for relevant information in a large volume of data needs advanced treatments. Medical data is a special type of data because it comes from different sources and in different formats and encapsulates medical knowledge. Personalized retrieval is necessary when it comes to medical data management. In fact, the patient’s medical record needs to be taken into account in order to offer relevant documents since it contains his/her medical history. The proposed approach offers an ontology building process based on the patient’s medical record. The built ontology is then used for personalized information retrieval as well as user similarity computation. The approach is composed of three layers: (1) Data layer, (2) Treatment layer and (3) Semantic layer and offers three treatments: (1) Ontology building, (2) Query reformulation and (3) User similarity computation. An application supporting all three layers has been implemented and it allowed an experimental evaluation of the proposal. The results show an improvement in the relevancy of returned medical documents.

Keywords: Personalized information retrieval; ontology building; medical data; NoSQL; big data (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1142/S0219649220500410

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