@inproceedings{tuggener-etal-2021-summarizing,
title = "Are We Summarizing the Right Way? A Survey of Dialogue Summarization Data Sets",
author = "Tuggener, Don and
Mieskes, Margot and
Deriu, Jan and
Cieliebak, Mark",
editor = "Carenini, Giuseppe and
Cheung, Jackie Chi Kit and
Dong, Yue and
Liu, Fei and
Wang, Lu",
booktitle = "Proceedings of the Third Workshop on New Frontiers in Summarization",
month = nov,
year = "2021",
address = "Online and in Dominican Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.newsum-1.12",
doi = "10.18653/v1/2021.newsum-1.12",
pages = "107--118",
abstract = "Dialogue summarization is a long-standing task in the field of NLP, and several data sets with dialogues and associated human-written summaries of different styles exist. However, it is unclear for which type of dialogue which type of summary is most appropriate. For this reason, we apply a linguistic model of dialogue types to derive matching summary items and NLP tasks. This allows us to map existing dialogue summarization data sets into this model and identify gaps and potential directions for future work. As part of this process, we also provide an extensive overview of existing dialogue summarization data sets.",
}
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<abstract>Dialogue summarization is a long-standing task in the field of NLP, and several data sets with dialogues and associated human-written summaries of different styles exist. However, it is unclear for which type of dialogue which type of summary is most appropriate. For this reason, we apply a linguistic model of dialogue types to derive matching summary items and NLP tasks. This allows us to map existing dialogue summarization data sets into this model and identify gaps and potential directions for future work. As part of this process, we also provide an extensive overview of existing dialogue summarization data sets.</abstract>
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%0 Conference Proceedings
%T Are We Summarizing the Right Way? A Survey of Dialogue Summarization Data Sets
%A Tuggener, Don
%A Mieskes, Margot
%A Deriu, Jan
%A Cieliebak, Mark
%Y Carenini, Giuseppe
%Y Cheung, Jackie Chi Kit
%Y Dong, Yue
%Y Liu, Fei
%Y Wang, Lu
%S Proceedings of the Third Workshop on New Frontiers in Summarization
%D 2021
%8 November
%I Association for Computational Linguistics
%C Online and in Dominican Republic
%F tuggener-etal-2021-summarizing
%X Dialogue summarization is a long-standing task in the field of NLP, and several data sets with dialogues and associated human-written summaries of different styles exist. However, it is unclear for which type of dialogue which type of summary is most appropriate. For this reason, we apply a linguistic model of dialogue types to derive matching summary items and NLP tasks. This allows us to map existing dialogue summarization data sets into this model and identify gaps and potential directions for future work. As part of this process, we also provide an extensive overview of existing dialogue summarization data sets.
%R 10.18653/v1/2021.newsum-1.12
%U https://aclanthology.org/2021.newsum-1.12
%U https://doi.org/10.18653/v1/2021.newsum-1.12
%P 107-118
Markdown (Informal)
[Are We Summarizing the Right Way? A Survey of Dialogue Summarization Data Sets](https://aclanthology.org/2021.newsum-1.12) (Tuggener et al., NewSum 2021)
ACL