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GFKL
2005
Springer

A Hybrid Machine Learning Approach for Information Extraction from Free Text

9 years 11 months ago
A Hybrid Machine Learning Approach for Information Extraction from Free Text
Abstract. We present a hybrid machine learning approach for information extraction from unstructured documents by integrating a learned classifier based on the Maximum Entropy Modeling (MEM), and a classifier based on our work on Data–Oriented Parsing (DOP). The hybrid behavior is achieved through a voting mechanism applied by an iterative tag–insertion algorithm. We have tested the method on a corpus of German newspaper articles about company turnover, and achieved 85.2% F-measure using the hybrid approach, compared to 79.3% for MEM
Günter Neumann
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where GFKL
Authors Günter Neumann
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