Ontology driven semantic profiling and retrieval in medical information systems

  • Authors:

  • Mehul Bhatt;Wenny Rahayu;Sury Prakash Soni;Carlo Wouters

  • Affiliations:

  • Cognitive Systems, Universität Bremen, 28359 Bremen, Germany;Data Engineering and Knowledge Management Group, Department of Computer Science and Computer Engineering, La Trobe University, Australia;Data Engineering and Knowledge Management Group, Department of Computer Science and Computer Engineering, La Trobe University, Australia;Data Engineering and Knowledge Management Group, Department of Computer Science and Computer Engineering, La Trobe University, Australia

  • Venue:
  • Web Semantics: Science, Services and Agents on the World Wide Web
  • Year:
  • 2009

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Abstract

We propose the application of a novel sub-ontology extraction methodology for achieving interoperability and improving the semantic validity of information retrieval in the medical information systems (MIS) domain. The system offers advanced profiling of a user's field of specialization by exploiting the concept of sub-ontology extraction, i.e., each sub-ontology may subsequently represent a particular user profile. Semantic profiling of a user's field of specialization or interest is necessary functionality in any medical domain information retrieval system; this is because the (structural and semantic) extent of information sources is massive and individual users are only likely to be interested in specific parts of the overall knowledge documents on the basis of their area of specialization. The prototypical system, OntoMOVE, has been specifically designed for application in the medical information systems domain. OntoMOVE utilizes semantic web standards like RDF(S) and OWL in addition to medical domain standards and vocabularies encompassed by the UMLS knowledge sources.