Contextdependent variation in word usage can be accounted for by leveraging multiple latent categorization systems.
cross-cutting models can be used to capture both syntagmatic and paradigmatic notions of word relatedness, breaking up word features into multiple categorization systems and then computing similarity separately for each system.