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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/985

Title: Learning (k,l)-Contextual Tree Languages for Information Extraction
Authors: Raeymaekers, S.
Bruynooghe, M.
Issue Date: 2005
Publisher: Springer
Citation: Machine Learning: ECML 2005. p. 305-316
Series/Report: Lecture Notes in Computer Science, 3720
Abstract: This paper introduces a novel method for learning a wrapper for extraction of text nodes from web pages based upon (k,l)-contextual tree languages. It also introduces a method to learn good values of k and l based on a few positive and negative examples. Finally, it describes how the algorithm can be integrated in a tool for information extraction.
URI: http://hdl.handle.net/1942/985
DOI: 10.1007/11564096_31
ISI #: 000233235200031
ISBN: 3-540-29243-8
ISSN: 0302-9743
Category: A1
Type: Journal Contribution
Validation: ecoom, 2006
Appears in Collections: Research publications

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