Combining Information Extraction Systems Using Voting and Stacked Generalization

@article{Sigletos2005CombiningIE,
  title={Combining Information Extraction Systems Using Voting and Stacked Generalization},
  author={Georgios Sigletos and Georgios Paliouras and Constantine D. Spyropoulos and Michael Hatzopoulos},
  journal={Journal of Machine Learning Research},
  year={2005},
  volume={6},
  pages={1751-1782}
}
This article investigates the effectiveness of voting and stacked generalization -also known as stackingin the context of information extraction (IE). A new stacking framework is proposed that accommodates well-known approaches for IE. The key idea is to perform cross-validation on the base-level data set, which consists of text documents annotated with relevant information, in order to create a meta-level data set that consists of feature vectors. A classifier is then trained using the new… CONTINUE READING
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