Similarity and dissimilarity are rarely formalized concepts in Artificial Intelligence (AI). Similarity and dissimilarity have a psychological origin, and they have been adapted to AI. In this field, however, similarity and dissimilarity choice is not always dependent on the problem to solve. In this paper, a formalization of similarity and dissimilarity is presented. The purpose of this paper is to contribute to the design and understanding of similarity and dissimilarity in AI, increasing their general utility. A formal definition and some basic properties are introduced. Also, some transformation functions and similarity and dissimilarity operators are presented.