This paper is a short introduction to our work on building and using folksonomies to facilitate communication between Semantic Web agents with disparate ontological representations. We briefly present the Semantic Matcher, a system that measures the semantic proximity between terms in interacting agents' ontologies at run-time, fully automatically and minimally: that is, only for semantic mismatches that impede communication. The system is designed to allow agents to "understand" the meanings of terms to be matched by comparing their folksonomy-based "mental representations".