Anti-Unification Based Learning of T-Wrappers for Information Extraction

نویسنده

  • Bernd Thomas
چکیده

We present a method for learning wrappers for multi-slot extraction from semi-structured documents. The presented method learns how to construct automatically wrappers from positive examples, consisting of text tuples occurring in the document. These wrappers (T-wrappers) are based on a feature structure unification based pattern language for information extraction. The presented technique is an inductive machine learning method based on a modified version of least general generalization ( TD-AntiUnification) for a subset of feature structures (tokens).

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تاریخ انتشار 2003