Paper: Graph-based Semi-Supervised Learning Algorithms for NLP

ACL ID P12-4006
Title Graph-based Semi-Supervised Learning Algorithms for NLP
Venue Annual Meeting of the Association of Computational Linguistics
Session Tutorial Abstracts
Year 2012
Authors

Tutorial Abstracts of ACL 2012, page 6, Jeju, Republic of Korea, 8 July 2012. c?2012 Association for Computational Linguistics Graph-based Semi-Supervised Learning Algorithms for NLP Amar Subramanya Google Research asubram@google.com Partha Pratim Talukdar Carnegie Mellon University ppt@cs.cmu.edu Abstract While labeled data is expensive to prepare, ever in- creasing amounts of unlabeled linguistic data are becoming widely available. In order to adapt to this phenomenon, several semi-supervised learning (SSL) algorithms, which learn from labeled as well as unlabeled data, have been developed. In a sep- arate line of work, researchers have started to real- ize that graphs provide a natural way to represent data in a variety of domains. Graph-based SSL al- gorithms, which bring together thes...