About: Learning to Select Important Context Words for Event Detection

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Learning to Select Important Context Words for Event Detection
Creator	Ngo Nguyen, Tuan Ngo, Nghia Nguyen, Thien
Source	PMC
abstract	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.
has issue date	2020-04-17(xsd:dateTime)
bibo:doi	10.1007/978-3-030-47436-2_57
has license	no-cc
sha1sum (hex)	47ab3f63bf2c26bea798542fc33b87ff85ac4dc3
schema:url	https://doi.org/10.1007/978-3-030-47436-2_57
resource representing a document's title	Learning to Select Important Context Words for Event Detection
has PubMed Central identifier	PMC7206272
schema:publication	Advances in Knowledge Discovery and Data Mining
resource representing a document's body	covid:47ab3f63bf2c26bea798542fc33b87ff85ac4dc3#body_text
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