Augmenting Mobile Localization with Activities and Common Sense Knowledge

  • Nicola Bicocchi
  • Gabriella Castelli
  • Marco Mamei
  • Franco Zambonelli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7040)


Location is a key element for ambient intelligence services. Due to GPS inaccuracies, inferring high level information (i.e., being at home, at work, in a restaurant) from geographic coordinates in still non trivial. In this paper we use information about activities being performed by the user to improve location recognition accuracy. Unlike traditional methods, relations between locations and activities are not extracted from training data but from an external commonsense knowledge base. Our approach maps location and activity labels to concepts organized within the ConceptNet network. Then, it verifies their commonsense proximity by implementing a bio-inspired greedy algorithm. Experimental results show a sharp increase in localization accuracy.


Activity Recognition Search Radius Activity Label Location Recognition Common Sense Knowledge 
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 2011

Authors and Affiliations

  • Nicola Bicocchi
    • 1
  • Gabriella Castelli
    • 2
  • Marco Mamei
    • 2
  • Franco Zambonelli
    • 2
  1. 1.Dipartimento di Ingegneria dell’InformazioneUniversitá di Modena e Reggio EmiliaItaly
  2. 2.Dipartimento di Scienze e Metodi dell’IngegneriaUniversitá di Modena e Reggio EmiliaItaly

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