Abstract
In this paper, a new model for aggregating multiple criteria evaluations for relevance assessment is proposed. An information retrieval context is considered, where relevance is modelled as a multidimensional property of documents. In the paper, the proposed aggregation operator is applied to define a model for personalized Information Retrieval (IR), in which four criteria are considered in order to assess 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 with 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.
In the paper, some preliminary experimental results are also reported.
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da Costa Pereira, C., Dragoni, M., Pasi, G. (2009). Multidimensional Relevance: A New Aggregation Criterion. In: Boughanem, M., Berrut, C., Mothe, J., Soule-Dupuy, C. (eds) Advances in Information Retrieval. ECIR 2009. Lecture Notes in Computer Science, vol 5478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00958-7_25
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DOI: https://doi.org/10.1007/978-3-642-00958-7_25
Publisher Name: Springer, Berlin, Heidelberg
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