A generalized axiomatic definition of information-theoretic similarity is provided for taxonomies that are structured as directed acyclic graph form which multiple terns may be used to describe an object. The definition is adaptable in the presence of ambiguity, as introduced by an evolving taxonomy or classifiers with imperfect knowledge, and two new similarity measures are introduced based on the definitions. A pragmatic implementation is also provided for similarity measures that arc tightly integrated with an object-relational database and scales to large taxonomies and large datasets.
