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Learning to Select Important Context Words for Event Detection

It is important to locate important context words in the sentences and model them appropriately to perform event detection (ED) effectively. This has been mainly achieved by some fixed word selection strategy in the previous studies for ED. In this work, we propose a novel method that learns to sele...

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Detalles Bibliográficos
Autores principales: Ngo, Nghia Trung, Nguyen, Tuan Ngo, Nguyen, Thien Huu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206272/
http://dx.doi.org/10.1007/978-3-030-47436-2_57
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author Ngo, Nghia Trung
Nguyen, Tuan Ngo
Nguyen, Thien Huu
author_facet Ngo, Nghia Trung
Nguyen, Tuan Ngo
Nguyen, Thien Huu
author_sort Ngo, Nghia Trung
collection PubMed
description It is important to locate important context words in the sentences and model them appropriately to perform event detection (ED) effectively. This has been mainly achieved by some fixed word selection strategy in the previous studies for ED. In this work, we propose a novel method that learns to select relevant context words for ED based on the Gumbel-Softmax trick. The extensive experiments demonstrate the effectiveness of the proposed method, leading to the state-of-the-art performance for ED over different benchmark datasets and settings.
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spelling pubmed-72062722020-05-08 Learning to Select Important Context Words for Event Detection Ngo, Nghia Trung Nguyen, Tuan Ngo Nguyen, Thien Huu Advances in Knowledge Discovery and Data Mining Article It is important to locate important context words in the sentences and model them appropriately to perform event detection (ED) effectively. This has been mainly achieved by some fixed word selection strategy in the previous studies for ED. In this work, we propose a novel method that learns to select relevant context words for ED based on the Gumbel-Softmax trick. The extensive experiments demonstrate the effectiveness of the proposed method, leading to the state-of-the-art performance for ED over different benchmark datasets and settings. 2020-04-17 /pmc/articles/PMC7206272/ http://dx.doi.org/10.1007/978-3-030-47436-2_57 Text en © Springer Nature Switzerland AG 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Ngo, Nghia Trung
Nguyen, Tuan Ngo
Nguyen, Thien Huu
Learning to Select Important Context Words for Event Detection
title Learning to Select Important Context Words for Event Detection
title_full Learning to Select Important Context Words for Event Detection
title_fullStr Learning to Select Important Context Words for Event Detection
title_full_unstemmed Learning to Select Important Context Words for Event Detection
title_short Learning to Select Important Context Words for Event Detection
title_sort learning to select important context words for event detection
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206272/
http://dx.doi.org/10.1007/978-3-030-47436-2_57
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