This chapter reviews some of the methods that incorporate prior knowledge in the process of finding semantic correspondences between 3D shapes. It shows how the problem can be formulated as the optimization of an energy function and compares the different variants of the formulation that have been proposed in the literature. The energy to be minimized by a semantic labeling process is composed of two types of terms: the unary (or data) term and the pairwise (or smoothness) term. The data term takes into consideration how likely it is that a given node has a specific label. The smoothness term considers the intramesh and intermesh connectivity between nodes. The chapter shows a few semantic labeling and correspondence examples. It concludes with a discussion on the methods that are not covered in detail and outlines some challenges to stimulate future research.