The limits of automatic summarisation according to ROUGE

Publikation: Konference artikel i Proceeding eller bog/rapport kapitelKonferencebidrag i proceedingsForskningpeer review

Abstrakt

This paper discusses some central caveats of summarisation, incurred in the use of
the ROUGE metric for evaluation, with respect to optimal solutions. The task is NPhard, of which we give the first proof. Still, as we show empirically for three central benchmark datasets for the task, greedy algorithms empirically seem to perform optimally according to the metric. Additionally, overall quality assurance is problematic: there is no natural upper bound on the quality of summarisation systems, and even humans are excluded from performing optimal summarisation.
OriginalsprogEngelsk
TitelProceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics
Antal sider5
Vol/bind2
ForlagAssociation for Computational Linguistics
Publikationsdato2017
Sider41–45
ISBN (Trykt)978-1-945626-34-0
StatusUdgivet - 2017
BegivenhedThe 15th Conference of the European Chapter of the Association for Computational Linguistics - Valencia, Spanien
Varighed: 3 apr. 20177 apr. 2017
http://eacl2017.org/

Konference

KonferenceThe 15th Conference of the European Chapter of the Association for Computational Linguistics
Land/OmrådeSpanien
ByValencia
Periode03/04/201707/04/2017
Internetadresse

Fingeraftryk

Dyk ned i forskningsemnerne om 'The limits of automatic summarisation according to ROUGE'. Sammen danner de et unikt fingeraftryk.

Citationsformater