Cart (Loading....) | Create Account
Close category search window

Semi-supervised learning for word sense disambiguation using parallel corpora

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Mo Yu ; MOE-MS Key Lab. of Natural Language Process. & Speech, Harbin Inst. of Technol., Harbin, China ; Shu Wang ; Conghui Zhu ; Tiejun Zhao

The Application of word sense disambiguation (WSD) methods based on supervised machine learning are limited by the difficulties in defining sense tags and acquiring labeled data for training. In this paper, the two problems of WSD are solved in a semi-supervised learning framework with the help of parallel corpora. The sense tags are defined automatically according to the results of word alignment on the parallel corpora. And label propagation, a graph-based semi-supervised algorithm, is employed. The experiments show that our method achieves great improvement on Chinese WSD tasks and the performances get significant growth when the scale of monolingual sentences is increasing.

Published in:

Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference on  (Volume:3 )

Date of Conference:

26-28 July 2011

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.