Paper
Time-dependent concepts: representation and reasoning using temporal description logics

https://doi.org/10.1016/S0169-023X(96)00036-5Get rights and content

Abstract

A time-dependent concept is a conceptual entity that is defined in terms of temporal relationships with other entities. For example, the concept of an action is defined in terms of a set of temporal relationships among states of a system. The concept of “widow”, in natural language, is defined in terms of events that have occurred in the past. Time-dependent concepts appear in several application areas, from natural language to diagnosis, from planning to data mining. An interesting issue in knowledge representation is how to formally represent and reason with these concepts. In this paper, we represent a family of formal representation languages obtained as an interval-based temporal extension of description logics. We illustrate the expressiveness of these formalisms in representing time-dependent concepts with respect to standard description logics and other extensions. We give some complexity results for reasoning problems and we propose approximate algorithms to compute subsumption among time-dependent concepts.

References (41)

  • S Bergamaschi et al.

    On taxonomic reasoning in conceptual design

    ACM Transactions on Database Systems

    (1992)
  • E Bertino et al.

    The integration of heterogeneous data management systems: Approaches based on the object-oriented paradigm

  • C Bettini

    Taxonomic reasoning on temporal descriptions

  • C Bettini

    Estensioni temporali dei linguaggi terminologici

  • C Bettini

    A family of temporal terminological logics

  • C Bettini

    A formalization of interval-based temporal subsumption in first order logic

  • C Bettini et al.

    Testing Complex Temporal Relationships Involving Multiple Granularities and Its Application to Data Mining

  • A Borgida

    Descriptions logics in data management

    IEEE Transactions on Knowledge and Data Engineering

    (October 1995)
  • A Borgida et al.

    CLASSIC: A structural data model for objects

    ACM SIGMOD RECORD

    (June 1989)
  • R.J Brachman et al.

    The tractability of subsumption in frame-based description languages

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