Fomba, Soumana, Zaraté, Pascale, Kilgour, Marc, Camilleri, Guy, Konate, Jacqueline and Tangara, Fana (2017) A Recommender System Based on Multi-Criteria Aggregation. International Journal of Decision Support System Technology, 9 (4). pp. 1-15.

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Abstract

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 multi-criteria 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 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.