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An Agent-Based Data Mining System for Ontology Evolution

  • Conference paper
On the Move to Meaningful Internet Systems: OTM 2009 Workshops (OTM 2009)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5872))

Abstract

We have developed an evidence-based mental health ontological model that represents mental health in multiple dimensions. The ongoing addition of new mental health knowledge requires a continual update of the Mental Health Ontology. In this paper, we describe how the ontology evolution can be realized using a multi-agent system in combination with data mining algorithms. We use the TICSA methodology to design this multi-agent system which is composed of four different types of agents: Information agent, Data Warehouse agent, Data Mining agents and Ontology agent. We use UML 2.1 sequence diagrams to model the collaborative nature of the agents and a UML 2.1 composite structure diagram to model the structure of individual agents. The Mental Heath Ontology has the potential to underpin various mental health research experiments of a collaborative nature which are greatly needed in times of increasing mental distress and illness.

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Author information

Authors and Affiliations

  1. Digital Ecosystems and Business Intelligence Institute, Curtin University of Technology, GPO Box U1987, Perth, 6845, Australia

    Maja Hadzic & Darshan Dillon

Authors
  1. Maja Hadzic
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  2. Darshan Dillon
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Editor information

Editors and Affiliations

  1. STARLab, Vrije Universiteit Brussel (VUB), Bldg G/10, Pleinlaan 2, 1050, Brussels, Belgium

    Robert Meersman

  2. Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegancedo S/N, 28660, Boadilla del Monte, Madrid, Spain

    Pilar Herrero

  3. DEBII - CBS, De Laeter Way, Curtin University of Technology, 6102, Bentley, WA, Australia

    Tharam Dillon

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Hadzic, M., Dillon, D. (2009). An Agent-Based Data Mining System for Ontology Evolution. In: Meersman, R., Herrero, P., Dillon, T. (eds) On the Move to Meaningful Internet Systems: OTM 2009 Workshops. OTM 2009. Lecture Notes in Computer Science, vol 5872. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05290-3_102

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  • DOI: https://doi.org/10.1007/978-3-642-05290-3_102

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05289-7

  • Online ISBN: 978-3-642-05290-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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