Temporal Knowledge Acquisition and Modeling

  • Cyril Faucher
  • Charles Teissèdre
  • Jean-Yves Lafaye
  • Frédéric Bertrand
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6317)


The objectives of this paper are to present, describe, and explain the foundations and the functionalities of a temporal knowledge acquisition and modeling solution workflow, which aims at acquiring temporal knowledge from texts in order to populate a constrained object model. We are using several models for temporal data, one of which is generic and employed as a pivot model between a linguistic representation and a calendar representation. The approach we propose is generic and has been tested against a real use case, in which input data is made of temporal properties defining when a given location (a theater, a restaurant, a shopping center, etc.) is open or closed. Most expressions entered are expressed in intension. Our models provide a core support to the system that linguistically analyses data entries, transforms them into extensive calendar information and allow users to control the quality of the system’s interpretation.


Temporal Knowledge Acquisition Temporal Data Modeling Linguistic Annotation Model Driven Engineering 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Cyril Faucher
    • 1
  • Charles Teissèdre
    • 2
    • 3
  • Jean-Yves Lafaye
    • 1
  • Frédéric Bertrand
    • 1
  1. 1.L3iUniversity of La RochelleFrance
  2. 2.MoDyCo – UMR 7114Paris Ouest Nanterre La Défense University – CNRSFrance
  3. 3.MondecaParisFrance

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