2007 HighAccuracyMethodForSemiSupInfExtr

(Tratz and Sanfilippo, 2007) ⇒ Stephen Tratz, Antonio Sanfilippo. (2007). “A high accuracy method for semi-supervised information extraction.” In: Proceeding NAACL-Short '07 Human Language Technologies (2007).

Subject Headings: Relation Recognition from Text Task

Notes

Cited By

~1 http://scholar.google.com/scholar?cites=14155715154106172902

Quotes

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. Semi-supervised 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 semi-supervised IE approach, without increasing resource requirements.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2007 HighAccuracyMethodForSemiSupInfExtr	Stephen Tratz Antonio Sanfilippo			A high accuracy method for semi-supervised information extraction			http://portal.acm.org/citation.cfm?id=1614151