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    <abstract>We envisioned responsive generic hierarchical text summarization with summaries organized by section and paragraph based on hierarchical structure topic models. But we had to be sure that topic models were stable for the sampled corpora. To that end we developed a methodology for aligning multiple hierarchical structure topic models run over the same corpus under similar conditions, calculating a representative centroid model, and reporting stability of the centroid model. We ran stability experiments for standard corpora and a development corpus of Global Warming articles. We found flat and hierarchical structures of two levels plus the root offer stable centroid models, but hierarchical structures of three levels plus the root didn’t seem stable enough for use in hierarchical summarization.</abstract>
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%0 Conference Proceedings
%T Topic Model Stability for Hierarchical Summarization
%A Miller, John
%A McCoy, Kathleen
%Y Wang, Lu
%Y Cheung, Jackie Chi Kit
%Y Carenini, Giuseppe
%Y Liu, Fei
%S Proceedings of the Workshop on New Frontiers in Summarization
%D 2017
%8 September
%I Association for Computational Linguistics
%C Copenhagen, Denmark
%F miller-mccoy-2017-topic
%X We envisioned responsive generic hierarchical text summarization with summaries organized by section and paragraph based on hierarchical structure topic models. But we had to be sure that topic models were stable for the sampled corpora. To that end we developed a methodology for aligning multiple hierarchical structure topic models run over the same corpus under similar conditions, calculating a representative centroid model, and reporting stability of the centroid model. We ran stability experiments for standard corpora and a development corpus of Global Warming articles. We found flat and hierarchical structures of two levels plus the root offer stable centroid models, but hierarchical structures of three levels plus the root didn’t seem stable enough for use in hierarchical summarization.
%R 10.18653/v1/W17-4509
%U https://aclanthology.org/W17-4509
%U https://doi.org/10.18653/v1/W17-4509
%P 64-73

Markdown (Informal)

[Topic Model Stability for Hierarchical Summarization](https://aclanthology.org/W17-4509) (Miller & McCoy, 2017)

• Topic Model Stability for Hierarchical Summarization (Miller & McCoy, 2017)

ACL

• John Miller and Kathleen McCoy. 2017. Topic Model Stability for Hierarchical Summarization. In Proceedings of the Workshop on New Frontiers in Summarization, pages 64–73, Copenhagen, Denmark. Association for Computational Linguistics.