Difference between revisions of "Robust Systems for Preposition Error Correction Using Wikipedia Revisions"

From Wikipedia Quality
Jump to: navigation, search
(Adding new article - Robust Systems for Preposition Error Correction Using Wikipedia Revisions)
 
(+ wikilinks)
Line 1: Line 1:
'''Robust Systems for Preposition Error Correction Using Wikipedia Revisions''' - scientific work related to Wikipedia quality published in 2013, written by Aoife Cahill, Nitin Madnani, Joel R. Tetreault and Diane Napolitano.
+
'''Robust Systems for Preposition Error Correction Using Wikipedia Revisions''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Aoife Cahill]], [[Nitin Madnani]], [[Joel R. Tetreault]] and [[Diane Napolitano]].
  
 
== Overview ==
 
== Overview ==
Authors show that existing methods for training preposition error correction systems, whether using well-edited text or error-annotated corpora, do not generalize across very different test sets. Authors present a new, large errorannotated corpus and use it to train systems that generalize across three different test sets, each from a different domain and with different error characteristics. This new corpus is automatically extracted from Wikipedia revisions and contains over one million instances of preposition corrections.
+
Authors show that existing methods for training preposition error correction systems, whether using well-edited text or error-annotated corpora, do not generalize across very different test sets. Authors present a new, large errorannotated corpus and use it to train systems that generalize across three different test sets, each from a different domain and with different error characteristics. This new corpus is automatically extracted from [[Wikipedia]] revisions and contains over one million instances of preposition corrections.

Revision as of 06:35, 28 November 2019

Robust Systems for Preposition Error Correction Using Wikipedia Revisions - scientific work related to Wikipedia quality published in 2013, written by Aoife Cahill, Nitin Madnani, Joel R. Tetreault and Diane Napolitano.

Overview

Authors show that existing methods for training preposition error correction systems, whether using well-edited text or error-annotated corpora, do not generalize across very different test sets. Authors present a new, large errorannotated corpus and use it to train systems that generalize across three different test sets, each from a different domain and with different error characteristics. This new corpus is automatically extracted from Wikipedia revisions and contains over one million instances of preposition corrections.