Title | A High Accuracy Method for Semi-supervised Information Extraction |
Publication Type | Conference Paper |
Year of Publication | 2007 |
Authors | Tratz S, Sanfilippo A |
Conference Name | NAACL HLT 2007 |
Publisher | Association for Computational Linguistics |
Keywords | information extraction |
Abstract | Customization to specific domains of discourse and/or user requirements is one of the greatest challenges for today’s Information Extraction (IE) systems. While demonstrably effective, both rule-based and supervised machine learning approaches to IE customization pose too high a burden on the user. Semisupervised learning approaches may in principle offer a more resource effective solution but are still insufficiently accurate to grant realistic application. We demonstrate that this limitation can be overcome by integrating fully-supervised learning techniques within a semisupervised IE approach, without increasing resource requirements. |
URL | http://acl.ldc.upenn.edu/n/n07/n07-2043.pdf |
- Log in or register to post comments
- Google Scholar