Corpus ID: 2300418

DKPro-UGD: A Flexible Data-Cleansing Approach to Processing User-Generated Discourse

@inproceedings{EckartdeCastilho2009DKProUGDAF,
  title={DKPro-UGD: A Flexible Data-Cleansing Approach to Processing User-Generated Discourse},
  author={Richard Eckart de Castilho and Iryna Gurevych},
  year={2009}
}
User-generated discourse from Web 2.0 poses particular challenges to natural language processing (NLP) due to its noise and error proneness. A data cleansing step preceding the analysis steps in an NLP pipeline can reduce the problems. While recent efforts provide general-purpose collections of UIMA-based analysis components, data cleansing seems not yet to be covered. The five-stage data cleansing approach proposed here offers a maximum of flexibility in identifying problematic artifacts… Expand
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