• Measurable, i.e., a criterion that allows its quantified measurement upon some
evaluation scale;
• Ordinal, i.e., a criterion that defines an ordered set of acceptable values that
allow its evaluation using a qualitative or a descriptive scale;
• Probabilistic, i.e., a criterion that uses probability distributions to represent uncertainty in its evaluation;
• Fuzzy, i.e., a criterion whose evaluation is represented in relation to its possibility to belong in one of the intervals of a qualitative or descriptive evaluation
scale.
From a broad perspective, a family of criteria can be used to facilitate the representation of user preferences in recommender systems as well. Therefore, we can assume that all types of criteria could be potentially engaged in multi-criteria recommender systems, although (as shown later) it seems that some types are used in
currently developed systems more often than others