A Recommender System Based on Multi-Criteria Aggregation

Soumana Fomba, Pascale Zarate, Marc Kilgour, Guy Camilleri, Jacqueline Konate, Fana Tangara
2017 International Journal of Decision Support System Technology  
Recommender systems aim to support decision-makers by providing decision advice. We review briefly tools of Multi-Criteria Decision Analysis (MCDA), including aggregation operators, that could be the basis for a recommender system. Then we develop a multicriteria recommender system, STROMa (SysTem of RecOmmendation Multi-criteria), to support decisions by aggregating measures of performance contained in a performance matrix. The system makes inferences about preferences using a partial order on
more » ... criteria input by the decision-maker. To determine a total ordering of the alternatives, STROMa uses a multi-criteria aggregation operator, the Choquet integral of a fuzzy measure. Thus, recommendations are calculated using partial preferences provided by the decision maker and updated by the system. An integrated web platform is under development.
doi:10.4018/ijdsst.2017100101 fatcat:rmluljelljghvbed7u3d3kye4y