A novel approach for ontology-based dimensionality reduction for web text document classification

@article{Elhadad2017ANA,
  title={A novel approach for ontology-based dimensionality reduction for web text document classification},
  author={Mohamed K. Elhadad and Khaled M. Badran and Gouda I. Salama},
  journal={2017 IEEE/ACIS 16th International Conference on Computer and Information Science (ICIS)},
  year={2017},
  pages={373-378}
}
Dimensionality reduction of feature vector size plays a vital role in enhancing the text processing capabilities; it aims in reducing the size of the feature vector used in the mining tasks (classification, clustering… etc.). This paper proposes an efficient approach to be used in reducing the size of the feature vector for web text document classification process. This approach is based on using WordNet ontology, utilizing the benefit of its hierarchal structure, to eliminate words from the… CONTINUE READING