Paper Info
Title
Learning A Lexical Simplifier Using Wikipedia
Abstract
In this paper we introduce a new lexical simplification approach. We extract over 30K candidate lexical simplifications by identifying aligned words in a sentence-aligned corpus of English Wikipedia with Simple English Wikipedia. To apply these rules, we learn a feature-based ranker using SVMnk trained on a set of labeled simplifications collected using Amazon's Mechanical Turk. Using human simplifications for evaluation, we achieve a precision of 76% with changes in 86% of the examples.
Year
Venue
Field
2014
PROCEEDINGS OF THE 52ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 2
Computer science,Lexical simplification,Artificial intelligence,Natural language processing
DocType
Volume
Citations 
Conference
P14-2
15
PageRank 
References 
Authors
0.75
11
3
Name
Order
Citations
PageRank
Colby Horn1150.75
Cathryn Manduca2150.75
David Kauchak336325.92