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13

GFKL
2005
Springer

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A Hybrid Machine Learning Approach for Information Extraction from Free Text

13 years 10 months ago

A Hybrid Machine Learning Approach for Information Extraction from Free Text

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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

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GFKL 2005 | Hybrid Behavior | Iterative Tag–insertion Algorithm | Machine Learning Approach |

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Added	27 Jun 2010
Updated	27 Jun 2010
Type	Conference
Year	2005
Where	GFKL
Authors	Günter Neumann

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