Multidimensional relevance: Prioritized aggregation in a personalized Information Retrieval setting

  • Authors:

  • Célia da Costa Pereira;Mauro Dragoni;Gabriella Pasi

  • Affiliations:

  • Université de Nice Sophia-Antipolis/CNRS UMR-6070, Laboratoire I3S, 06903 Sophia Antipolis, France;Fondazione Bruno Kessler, FBK-irst Via Sommarive 18, Povo, I-38123 Trento, Italy;Universití degli Studi di Milano Bicocca, DISCO Viale Sarca 336, I-20126 Milano (MI), Italy

  • Venue:
  • Information Processing and Management: an International Journal
  • Year:
  • 2012

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Abstract

A new model for aggregating multiple criteria evaluations for relevance assessment is proposed. An Information Retrieval context is considered, where relevance is modeled as a multidimensional property of documents. The usefulness and effectiveness of such a model are demonstrated by means of a case study on personalized Information Retrieval with multi-criteria relevance. The following criteria are considered to estimate document relevance: aboutness, coverage, appropriateness, and reliability. The originality of this approach lies in the aggregation of the considered criteria in a prioritized way, by considering the existence of a prioritization relationship over the criteria. Such a prioritization is modeled by making the weights associated to a criterion dependent upon the satisfaction of the higher-priority criteria. This way, it is possible to take into account the fact that the weight of a less important criterion should be proportional to the satisfaction degree of the more important criterion. Experimental evaluations are also reported.