Multidimensional Relevance: Prioritized Aggregation in a Personalized Information Retrieval Setting - Archive ouverte HAL Access content directly
Journal Articles Information Processing and Management Year : 2012

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
Fichier principal
Vignette du fichier
infprocman.pdf (535.03 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01330089 , version 1 (09-06-2016)

Identifiers

Cite

Célia da Costa Pereira, Mauro Dragoni, Gabriella Pasi. Multidimensional Relevance: Prioritized Aggregation in a Personalized Information Retrieval Setting. Information Processing and Management, 2012, 48 (2), pp.340-357. ⟨10.1016/j.ipm.2011.07.001⟩. ⟨hal-01330089⟩
90 View
318 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More