Aker, A., Paramita, M., Kurtic, E. et al. (4 more authors) (2016) Automatic Label Generation for News Comment Clusters. In: Proceedings of the 9th International Natural Language Generation Conference. 9th International Natural Language Generation Conference (INLG 2016), 05-08 Sep 2016, Edinburgh, UK. Association for Computational Linguistics , pp. 61-69.
Abstract
We present a supervised approach to automat- ically labelling topic clusters of reader com- ments to online news. We use a feature set that includes both features capturing proper- ties local to the cluster and features that cap- ture aspects from the news article and from comments outside the cluster. We evaluate the approach in an automatic and a manual, task-based setting. Both evaluations show the approach to outperform a baseline method, which uses tf*idf to select comment-internal terms for use as topic labels. We illustrate how cluster labels can be used to generate cluster summaries and present two alternative sum- mary formats: a pie chart summary and an ab- stractive summary.
Metadata
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Copyright, Publisher and Additional Information: | © 2016 Association for Computational Linguistics. Licensed on a Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/). | ||||
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Institution: | The University of Sheffield | ||||
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) | ||||
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Depositing User: | Symplectic Sheffield | ||||
Date Deposited: | 15 Jun 2017 13:50 | ||||
Last Modified: | 19 Dec 2022 13:36 | ||||
Published Version: | https://doi.org/10.18653/v1/W16-6610 | ||||
Status: | Published | ||||
Publisher: | Association for Computational Linguistics | ||||
Identification Number: | https://doi.org/10.18653/v1/W16-6610 | ||||
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