SWAT: A System for Detecting Salient Wikipedia Entities in Texts
April 10, 2018 Β· Declared Dead Β· π International Conference on Climate Informatics
"No code URL or promise found in abstract"
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Authors
Marco Ponza, Paolo Ferragina, Francesco Piccinno
arXiv ID
1804.03580
Category
cs.IR: Information Retrieval
Citations
19
Venue
International Conference on Climate Informatics
Last Checked
4 months ago
Abstract
We study the problem of entity salience by proposing the design and implementation of SWAT, a system that identifies the salient Wikipedia entities occurring in an input document. SWAT consists of several modules that are able to detect and classify on-the-fly Wikipedia entities as salient or not, based on a large number of syntactic, semantic and latent features properly extracted via a supervised process which has been trained over millions of examples drawn from the New York Times corpus. The validation process is performed through a large experimental assessment, eventually showing that SWAT improves known solutions over all publicly available datasets. We release SWAT via an API that we describe and comment in the paper in order to ease its use in other software.
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