Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen: https://doi.org/10.21256/zhaw-23506
Publikationstyp: Konferenz: Paper
Art der Begutachtung: Peer review (Publikation)
Titel: Are we summarizing the right way? : a survey of dialogue summarization data sets
Autor/-in: Tuggener, Don
Mieskes, Margot
Deriu, Jan Milan
Cieliebak, Mark
et. al: No
DOI: 10.21256/zhaw-23506
Tagungsband: Proceedings of the Third Workshop on New Frontiers in Summarization
Seite(n): 107
Seiten bis: 118
Angaben zur Konferenz: Conference on Empirical Methods in Natural Language Processing (EMNLP), Punta Cana, Dominican Republic (online), 7-11 November 2021
Erscheinungsdatum: Nov-2021
Verlag / Hrsg. Institution: Association for Computational Linguistics
Sprache: Englisch
Schlagwörter: Natural Language Processing; Summarization; Dialoge Summarization; Survey
Fachgebiet (DDC): 006: Spezielle Computerverfahren
410.285: Computerlinguistik
Zusammenfassung: 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.
URI: https://aclanthology.org/2021.newsum-1.12/
https://digitalcollection.zhaw.ch/handle/11475/23506
Volltext Version: Publizierte Version
Lizenz (gemäss Verlagsvertrag): CC BY 4.0: Namensnennung 4.0 International
Departement: School of Engineering
Organisationseinheit: Centre for Artificial Intelligence (CAI)
Publiziert im Rahmen des ZHAW-Projekts: Interscriber: Turning Dialogues into Actionable Insights
Enthalten in den Sammlungen:Publikationen School of Engineering

Dateien zu dieser Ressource:
Datei Beschreibung GrößeFormat 
2021_Tuggener_Are_We_Summarizing_the_Right_Way_ACL.pdf262.13 kBAdobe PDFMiniaturbild
Öffnen/Anzeigen
Zur Langanzeige
Tuggener, D., Mieskes, M., Deriu, J. M., & Cieliebak, M. (2021). Are we summarizing the right way? : a survey of dialogue summarization data sets [Conference paper]. Proceedings of the Third Workshop on New Frontiers in Summarization, 107–118. https://doi.org/10.21256/zhaw-23506
Tuggener, D. et al. (2021) ‘Are we summarizing the right way? : a survey of dialogue summarization data sets’, in Proceedings of the Third Workshop on New Frontiers in Summarization. Association for Computational Linguistics, pp. 107–118. Available at: https://doi.org/10.21256/zhaw-23506.
D. Tuggener, M. Mieskes, J. M. Deriu, and M. Cieliebak, “Are we summarizing the right way? : a survey of dialogue summarization data sets,” in Proceedings of the Third Workshop on New Frontiers in Summarization, Nov. 2021, pp. 107–118. doi: 10.21256/zhaw-23506.
TUGGENER, Don, Margot MIESKES, Jan Milan DERIU und Mark CIELIEBAK, 2021. Are we summarizing the right way? : a survey of dialogue summarization data sets. In: Proceedings of the Third Workshop on New Frontiers in Summarization [online]. Conference paper. Association for Computational Linguistics. November 2021. S. 107–118. Verfügbar unter: https://aclanthology.org/2021.newsum-1.12/
Tuggener, Don, Margot Mieskes, Jan Milan Deriu, and Mark Cieliebak. 2021. “Are We Summarizing the Right Way? : A Survey of Dialogue Summarization Data Sets.” Conference paper. In Proceedings of the Third Workshop on New Frontiers in Summarization, 107–18. Association for Computational Linguistics. https://doi.org/10.21256/zhaw-23506.
Tuggener, Don, et al. “Are We Summarizing the Right Way? : A Survey of Dialogue Summarization Data Sets.” Proceedings of the Third Workshop on New Frontiers in Summarization, Association for Computational Linguistics, 2021, pp. 107–18, https://doi.org/10.21256/zhaw-23506.


Alle Ressourcen in diesem Repository sind urheberrechtlich geschützt, soweit nicht anderweitig angezeigt.