Abstract
A large number of Web information extraction algorithms are based on machine learning techniques. For such extraction algorithms, we propose employing a lazy learning strategy to build a specialized model for each test instance to improve the extraction accuracy and avoid the disadvantages of constructing a single general model.
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Ozcan, R., Altingovde, I.S., Ulusoy, Ö. (2012). In Praise of Laziness: A Lazy Strategy for Web Information Extraction. In: Baeza-Yates, R., et al. Advances in Information Retrieval. ECIR 2012. Lecture Notes in Computer Science, vol 7224. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28997-2_65
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DOI: https://doi.org/10.1007/978-3-642-28997-2_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28996-5
Online ISBN: 978-3-642-28997-2
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