A Multidimensional and Multigranular Model of Time for Medical Knowledge-Based Systems

  • Authors:

  • Elpida T. Keravnou

  • Affiliations:

  • Department of Computer Science, University of Cyprus, P.O. Box 20537, CY-1678 Nicosia, Cyprus. elpida@ucy.ac.cy

  • Venue:
  • Journal of Intelligent Information Systems - Special issue on integrating artificial intelligene and database technologies
  • Year:
  • 1999

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Abstract

In temporal reasoning there are two interrelated issues;how to model time per se and how to model occurrences. In medical temporal reasoning the need for multiple granularitiesand multiple conceptual temporal contexts arises in relationto a model of time. Some occurrence can then be expressedwith respect to different temporal contexts. This paper presents a multidimensional and multigranular modelof time for knowledge-based problem solving, primarily formedical applications. Both the conceptual issues and the design issues underlying theimplementation of the proposed model are discussed. The presented model of time has been developed in the context of atime ontology for medical knowledge engineering, whose principalprimitives are the time-axis and the time-object. The notion of a time-axis constitutes the primitive for the proposedmodel of time, while the notion of a time-objectaims to integrate time with other essential forms ofknowledge, such as structural and causal knowledge,in the expression of differenttypes of occurrences, thus resulting in the integral embodiment of timein such occurrences. The notion of a time-object and the overall ontology of occurrencesis given only a cursory mention in this paper. The focus of the paper is the time model. More specifically,the paper presents the notion of a time-axis in the contextof the overall time ontology and discusses at length the twoclasses of time-axes, namely the atomic axes and the spanning axes. The assertion language which has been developed, for the entireontology, for the expressionof axioms (deductive rules and integrity constraints), attributeconstraints and propagation methods is presented and illustrated. The implementation of the time model in terms of a layeredobject-based system is also presented.