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NLPRS
2001
Springer

Hierarchical Concept Description and Learning for Information Extraction

8 years 9 months ago
Hierarchical Concept Description and Learning for Information Extraction
This paper addresses the problem of extracting information from textual documents, either normal documents or web pages. A new approach for extracting complicate information from semi-structured documents is introduced that exploits a successive hierarchical rule-learning algorithm. Through evaluation it is shown that this approach can extract complicate concepts with a much higher precision than the equivalent rule learning applied to flat text. In addition, the rate of learning is significantly higher for the hierarchical approach.
Luo Xiao, Dieter Wissmann, Michael Brown, Stefan J
Added 30 Jul 2010
Updated 30 Jul 2010
Type Conference
Year 2001
Where NLPRS
Authors Luo Xiao, Dieter Wissmann, Michael Brown, Stefan Jablonski
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