Characterizing Nexus of Similarity between Entities

Similarities play a significant role in diverse real-world scenarios. Researchers across various fields have proposed different methodologies for measuring entity similarity and expanding sets of entities with similar ones. As a result, modern machines are adept at performing these tasks by taking in some regard relevant interconnected properties shared by entities, which we refer to as nexus of similarity. To complement existing approaches, we present a very general logic-based framework, equipped with a suitable formal semantics, for characterizing nexus of similarity between (tuples of) entities of any knowledge base, namely express such nexus, formally and comprehensively, in a manner that they are both understandable to machines and humans.