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        <title>Improving ROUGE for Timeline Summarization</title>
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            <namePart type="given">Mirella</namePart>
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            <namePart type="given">Alexander</namePart>
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    <abstract>Current evaluation metrics for timeline summarization either ignore the temporal aspect of the task or require strict date matching. We introduce variants of ROUGE that allow alignment of daily summaries via temporal distance or semantic similarity. We argue for the suitability of these variants in a theoretical analysis and demonstrate it in a battery of task-specific tests.</abstract>
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%0 Conference Proceedings
%T Improving ROUGE for Timeline Summarization
%A Martschat, Sebastian
%A Markert, Katja
%Y Lapata, Mirella
%Y Blunsom, Phil
%Y Koller, Alexander
%S Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
%D 2017
%8 April
%I Association for Computational Linguistics
%C Valencia, Spain
%F martschat-markert-2017-improving
%X Current evaluation metrics for timeline summarization either ignore the temporal aspect of the task or require strict date matching. We introduce variants of ROUGE that allow alignment of daily summaries via temporal distance or semantic similarity. We argue for the suitability of these variants in a theoretical analysis and demonstrate it in a battery of task-specific tests.
%U https://aclanthology.org/E17-2046
%P 285-290

Markdown (Informal)

[Improving ROUGE for Timeline Summarization](https://aclanthology.org/E17-2046) (Martschat & Markert, EACL 2017)

• Improving ROUGE for Timeline Summarization (Martschat & Markert, EACL 2017)

ACL

• Sebastian Martschat and Katja Markert. 2017. Improving ROUGE for Timeline Summarization. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 285–290, Valencia, Spain. Association for Computational Linguistics.