String Kernels for Polarity Classification: A Study Across Different Languages

@inproceedings{GimnezPrez2018StringKF,
  title={String Kernels for Polarity Classification: A Study Across Different Languages},
  author={Rosa M. Gim{\'e}nez-P{\'e}rez and Marc Franco-Salvador and Paolo Rosso},
  booktitle={NLDB},
  year={2018}
}
The polarity classification task has as objective to automatically deciding whether a subjective text is positive or negative. Using a cross-domain setting implies the use of different domains for the training and testing. Recently, string kernels, a method which does not employ domain adaptation techniques has been proposed. In this work, we analyse the performance of this method across four different languages: English, German, French and Japanese. Experimental results show the strong… 
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