@inproceedings{schluter-martinez-alonso-2016-approximate,
title = "Approximate unsupervised summary optimisation for selections of {ROUGE}",
author = "Schluter, Natalie and
Mart{\'\i}nez Alonso, H{\'e}ctor",
editor = "Danlos, Laurence and
Hamon, Thierry",
booktitle = "Actes de la conf{\'e}rence conjointe JEP-TALN-RECITAL 2016. volume 2 : TALN (Posters)",
month = "7",
year = "2016",
address = "Paris, France",
publisher = "AFCP - ATALA",
url = "https://aclanthology.org/2016.jeptalnrecital-poster.5",
pages = "349--354",
abstract = "Approximate summary optimisation for selections of ROUGE It is standard to measure automatic summariser performance using the ROUGE metric. Unfortunately, ROUGE is not appropriate for unsupervised summarisation approaches. On the other hand, we show that it is possible to optimise approximately for ROUGE-n by using a document-weighted ROUGE objective. Doing so results in state-of-the-art summariser performance for single and multiple document summaries for both English and French. This is despite a non-correlation of the documentweighted ROUGE metric with human judgments, unlike the original ROUGE metric. These findings suggest a theoretical approximation link between the two metrics.",
}
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<abstract>Approximate summary optimisation for selections of ROUGE It is standard to measure automatic summariser performance using the ROUGE metric. Unfortunately, ROUGE is not appropriate for unsupervised summarisation approaches. On the other hand, we show that it is possible to optimise approximately for ROUGE-n by using a document-weighted ROUGE objective. Doing so results in state-of-the-art summariser performance for single and multiple document summaries for both English and French. This is despite a non-correlation of the documentweighted ROUGE metric with human judgments, unlike the original ROUGE metric. These findings suggest a theoretical approximation link between the two metrics.</abstract>
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%0 Conference Proceedings
%T Approximate unsupervised summary optimisation for selections of ROUGE
%A Schluter, Natalie
%A Martínez Alonso, Héctor
%Y Danlos, Laurence
%Y Hamon, Thierry
%S Actes de la conférence conjointe JEP-TALN-RECITAL 2016. volume 2 : TALN (Posters)
%D 2016
%8 July
%I AFCP - ATALA
%C Paris, France
%F schluter-martinez-alonso-2016-approximate
%X Approximate summary optimisation for selections of ROUGE It is standard to measure automatic summariser performance using the ROUGE metric. Unfortunately, ROUGE is not appropriate for unsupervised summarisation approaches. On the other hand, we show that it is possible to optimise approximately for ROUGE-n by using a document-weighted ROUGE objective. Doing so results in state-of-the-art summariser performance for single and multiple document summaries for both English and French. This is despite a non-correlation of the documentweighted ROUGE metric with human judgments, unlike the original ROUGE metric. These findings suggest a theoretical approximation link between the two metrics.
%U https://aclanthology.org/2016.jeptalnrecital-poster.5
%P 349-354
Markdown (Informal)
[Approximate unsupervised summary optimisation for selections of ROUGE](https://aclanthology.org/2016.jeptalnrecital-poster.5) (Schluter & Martínez Alonso, JEP/TALN/RECITAL 2016)
ACL