Multicriteria aggregating operator adaptation based on decision making context

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 generic multi-criteria recommender system, to support decisions by aggregating measures of performance contained in a performance matrix. To determine a total order of alternatives, the system uses different multicriteria aggregation operators depending on the context of use of the system. Thus, recommendations are calculated using partial preferences provided by the decision maker and updated by the system. An integrated web platform is under development.