Time Integration in Semantic Trajectories Using an Ontological Modelling Approach

A Case Study with Experiments, Optimization and Evaluation of an Integration Approach
  • Rouaa Wannous
  • Jamal Malki
  • Alain Bouju
  • Cécile Vincent
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 185)


Nowadays, with a growing use of location-aware, wirelessly connected, mobile devices, we can easily capture trajectories of mobile objects. To exploit these raw trajectories, we need to enhance them with semantic information. Several research fields are currently focusing on semantic trajectories to support queries and inferences to help users for validating and discovering more knowledge about mobile objects. The inference mechanism is needed for queries on semantic trajectories connected to other sources of information. Time and space knowledge are fundamental sources of information used by the inference operation on semantic trajectories. This article presents a case study of inference mechanism on semantic trajectories. We propose a solution based on an ontological approach for modelling semantic trajectories integrating time information and rules. We give experiments and evaluations of the proposed approach on generated and real data.


Vectorial Axis Mobile Object Inference Mechanism Dive Duration Ontological Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Rouaa Wannous
    • 1
  • Jamal Malki
    • 1
  • Alain Bouju
    • 1
  • Cécile Vincent
    • 2
  1. 1.L3i Laboratory, EA 2118University of La RochelleLa RochelleFrance
  2. 2.LIENSs Laboratory, UMR 7266University of La RochelleLa RochelleFrance

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