You are here

A High Accuracy Method for Semi-supervised Information Extraction

TitleA High Accuracy Method for Semi-supervised Information Extraction
Publication TypeConference Paper
Year of Publication2007
AuthorsTratz, S, Sanfilippo, A
Conference NameNAACL HLT 2007
PublisherAssociation for Computational Linguistics
Keywordsinformation 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.

URLhttp://acl.ldc.upenn.edu/n/n07/n07-2043.pdf