Extracting Compact Sets of Features for Question Classification in Cognitive Systems: A Comparative Study

@article{Pota2015ExtractingCS,
  title={Extracting Compact Sets of Features for Question Classification in Cognitive Systems: A Comparative Study},
  author={Marco Pota and Angela Fuggi and Massimo Esposito and Giuseppe De Pietro},
  journal={2015 10th International Conference on P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC)},
  year={2015},
  pages={551-556}
}
Question Classification is one of the key tasks of Cognitive Systems based on the Question Answering paradigm. It aims at identifying the type of the possible answer for a question expressed in natural language. Machine learning techniques are typically employed for this task, and exploit a high number of features extracted from labelled questions of benchmark training sets in order to achieve good classification results. However, the high dimensionality of the feature space often limits the… CONTINUE READING