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NAACL
2007

A High Accuracy Method for Semi-Supervised Information Extraction

8 years 11 months ago
A High Accuracy Method for Semi-Supervised Information Extraction
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.
Stephen Tratz, Antonio Sanfilippo
Added 30 Oct 2010
Updated 30 Oct 2010
Type Conference
Year 2007
Where NAACL
Authors Stephen Tratz, Antonio Sanfilippo
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