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IEAAIE
2001
Springer

Selecting a Relevant Set of Examples to Learn IE-Rules

13 years 8 months ago
Selecting a Relevant Set of Examples to Learn IE-Rules
The growing availability of online text has lead to an increase in the use of automatic knowledge acquisition approaches from textual data, as in Information Extraction (IE). Some IE systems use knowledge learned by single-concept learning systems, as sets of IE rules. Most of such systems need both sets of positive and negative examples. However, the manual selection of positive examples can be a very hard task for experts, while automatic methods for selecting negative examples can generate extremely large example sets, in spite of the fact that only a small subset of them is relevant to learn. This paper brie y describes a more portable multi-concept learning system and presents a methodology to select a relevant set of training examples.
Jordi Turmo, Horacio Rodríguez
Added 30 Jul 2010
Updated 30 Jul 2010
Type Conference
Year 2001
Where IEAAIE
Authors Jordi Turmo, Horacio Rodríguez
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