Prioritized Aggregation of Multiple Context Dimensions in Mobile IR

  • Ourdia Bouidghaghen
  • Lynda Tamine-Lechani
  • Gabriella Pasi
  • Guillaume Cabanac
  • Mohand Boughanem
  • Célia da Costa Pereira
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7097)


An interesting aspect emerging in mobile information retrieval is related to the several contextual features that can be considered as new dimensions in the relevance assessment process. In this paper, we propose a multidimensional ranking model based on the three dimensions of topic, interest, and location. The peculiarity of our multidimensional ranking lies in a “prioritized combination” of the considered criteria, using the “prioritized scoring” and “prioritized and” operators, which allow flexible personalization of search results according to users’ preferences. In order to evaluate the effectiveness of our model, we propose a simulation based evaluation framework that investigates the integration of the contextual dimensions into the evaluation process. Extensive experimental results obtained by using our simulation framework show the effectiveness of our multidimensional personalized ranking model.


mobile IR multidimensional personalization contextual criteria prioritized aggregation simulation-based evaluation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ourdia Bouidghaghen
    • 1
  • Lynda Tamine-Lechani
    • 1
  • Gabriella Pasi
    • 2
  • Guillaume Cabanac
    • 1
  • Mohand Boughanem
    • 1
  • Célia da Costa Pereira
    • 3
  1. 1.IRIT-University Paul SabatierToulouseFrance
  2. 2.DISCOUniversità degli Studi di Milano BicoccaMilanoItaly
  3. 3.DTIUniversità degli Studi di MilanoItaly

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