Multidimensional Relevance: Prioritized Aggregation in a Personalized Information Retrieval Setting

Abstract : A new model for aggregating multiple criteria evaluations for relevance assessment is proposed. An Information Retrieval context is considered, where relevance is mod- eled 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
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Information Processing and Management, Elsevier, 2012, 48 (2), pp.340-357. 〈10.1016/j.ipm.2011.07.001〉
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Célia Da Costa Pereira, Mauro Dragoni, Gabriella Pasi. Multidimensional Relevance: Prioritized Aggregation in a Personalized Information Retrieval Setting. Information Processing and Management, Elsevier, 2012, 48 (2), pp.340-357. 〈10.1016/j.ipm.2011.07.001〉. 〈hal-01330089〉

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