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Automatic Evaluation of Local Topic Quality
2019
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
Topic models are typically evaluated with respect to the global topic distributions that they generate, using metrics such as coherence, but without regard to local (token-level) topic assignments. Token-level assignments are important for downstream tasks such as classification. Recent models, which claim to improve token-level topic assignments, are only validated on global metrics. We elicit human judgments of token-level topic assignments: over a variety of topic model types and parameters,
doi:10.18653/v1/p19-1076
dblp:conf/acl/LundAFCBBS19
fatcat:e5aud6ljmveu3neh5yue7sympi