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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/8318

Title: Learning (k, l)-contextual tree languages for information extraction from web pages
Authors: Raeymaekers, Stefan
Bruynooghe, Maurice
Issue Date: 2008
Publisher: SPRINGER
Citation: MACHINE LEARNING, 71(2-3). p. 155-183
Abstract: This paper introduces a novel method for learning a wrapper for extraction of information from web pages, based upon (k, l)-contextual tree languages. It also introduces a method to learn good values of k and I based on a few positive and negative examples. Finally, it describes how the algorithm can be integrated in a tool for information extraction.
Notes: Katholieke Univ Leuven, Dept Comp Sci, B-3001 Louvain, Belgium. Univ Hasselt & Transnatl Univ Limburg, B-3590 Diepenbeek, Belgium.
URI: http://hdl.handle.net/1942/8318
ISI #: 000255788300002
ISSN: 0885-6125
Category: A1
Type: Journal Contribution
Validation: ecoom, 2009
Appears in Collections: Research publications

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