Learning (k, l)-Contextual Tree Languages for Information Extraction

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.

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