FML-based ontological agent for healthcare application with diabetes

G. Acampora, C.-S. Lee, M.-H. Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

6 Citations (Scopus)


It is well-known that classical ontologies are not sufficient to deal with imprecise and vague knowledge. On the other hand, fuzzy ontologies can effectively solve data and knowledge with uncertainty, most importantly, if they are integrated with innovative methods for developing agents’ intelligence as the Fuzzy Markup Language (FML). In this paper, an FML-based ontology-based intelligent fuzzy agent and a semantic decision making mechanism are proposed to apply to the semantic decision making for diabetes domain. The FML-based definition is considered modeling the knowledge base and rule base of the fuzzy objects and inference operators. The experimental results show that the proposed method is feasible for diabetes semantic decision-making.
Original languageEnglish
Title of host publicationProceedings of the IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, WI-IAT '09, 15-18 September 2009, Milan, Italy
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Print)978-1-4244-5331-3
Publication statusPublished - 2009


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