Ranking features by means of a qualitative optimization process: Artificial intelligence research and development

John A. Dawson, Yu-Chiang Hu, Francesc Prats Duaygues, Rosario Rovira Llobera, Mònica Sánchez Soler, Josep Sayeras Maspera

Producció científica: Capítol de llibreCapítol

Resum

A set of qualitative measures describing a retail firm is considered. A qualitative ranking process of these features based on the managers' evaluations is presented. In a decision making context, this paper proposes a methodology to synthesise information given by ordinal data. Features are evaluated by each manager on an ordinal scale with different levels of precision and from two points of view: importance of the measure and performance on the measure. A representation for the different evaluations by means of k-dimensional qualitative orders of magnitude labels is proposed. The presented methodology deals with these evaluations to obtain two rankings based on comparing distances against a reference k-dimensional label. The final ranking of features with respect to their importance will help the managers to make decisions to improve the performance.
Idioma originalAnglès
Títol de la publicacióArtificial intelligence research and development
Pàgines310-322
Estat de la publicacióPublicada - 1 d’oct. 2007

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