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    <abstract>Multilingual topic models enable document analysis across languages through coherent multilingual summaries of the data. However, there is no standard and effective metric to evaluate the quality of multilingual topics. We introduce a new intrinsic evaluation of multilingual topic models that correlates well with human judgments of multilingual topic coherence as well as performance in downstream applications. Importantly, we also study evaluation for low-resource languages. Because standard metrics fail to accurately measure topic quality when robust external resources are unavailable, we propose an adaptation model that improves the accuracy and reliability of these metrics in low-resource settings.</abstract>
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%0 Conference Proceedings
%T Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation
%A Hao, Shudong
%A Boyd-Graber, Jordan
%A Paul, Michael J.
%Y Walker, Marilyn
%Y Ji, Heng
%Y Stent, Amanda
%S Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
%D 2018
%8 June
%I Association for Computational Linguistics
%C New Orleans, Louisiana
%F hao-etal-2018-lessons
%X Multilingual topic models enable document analysis across languages through coherent multilingual summaries of the data. However, there is no standard and effective metric to evaluate the quality of multilingual topics. We introduce a new intrinsic evaluation of multilingual topic models that correlates well with human judgments of multilingual topic coherence as well as performance in downstream applications. Importantly, we also study evaluation for low-resource languages. Because standard metrics fail to accurately measure topic quality when robust external resources are unavailable, we propose an adaptation model that improves the accuracy and reliability of these metrics in low-resource settings.
%R 10.18653/v1/N18-1099
%U https://aclanthology.org/N18-1099
%U https://doi.org/10.18653/v1/N18-1099
%P 1090-1100

Markdown (Informal)

[Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation](https://aclanthology.org/N18-1099) (Hao et al., NAACL 2018)

• Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation (Hao et al., NAACL 2018)

ACL

• Shudong Hao, Jordan Boyd-Graber, and Michael J. Paul. 2018. Lessons from the Bible on Modern Topics: Low-Resource Multilingual Topic Model Evaluation. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), pages 1090–1100, New Orleans, Louisiana. Association for Computational Linguistics.