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An Automatic Approach for Document-level Topic Model Evaluation

2017-06-16 · CONLL 2017 8 · Shraey Bhatia, Jey Han Lau, Timothy Baldwin

Topic models jointly learn topics and document-level topic distribution. Extrinsic evaluation of topic models tends to focus exclusively on topic-level evaluation, e.g. by assessing the coherence of topics. We demonstrate that there can be large discrepancies between topic- and document-level model quality, and that basing model evaluation on topic-level analysis can be highly misleading. We propose a method for automatically predicting topic model quality based on analysis of document-level topic allocations, and provide empirical evidence for its robustness.

📄 PDF Abstract BibTeX arXiv:1706.05140

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Topic Models

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