Taming Wild High Dimensional Text Data with a Fuzzy Lash

@article{Karami2017TamingWH,
  title={Taming Wild High Dimensional Text Data with a Fuzzy Lash},
  author={Amir Karami},
  journal={2017 IEEE International Conference on Data Mining Workshops (ICDMW)},
  year={2017},
  pages={518-522}
}
  • A. Karami
  • Published 1 November 2017
  • Computer Science, Mathematics
  • 2017 IEEE International Conference on Data Mining Workshops (ICDMW)
The bag of words (BOW) represents a corpus in a matrix whose elements are the frequency of words. However, each row in the matrix is a very high-dimensional sparse vector. Dimension reduction (DR) is a popular method to address sparsity and high-dimensionality issues. Among different strategies to develop DR method, Unsupervised Feature Transformation (UFT) is a popular strategy to map all words on a new basis to represent BOW. The recent increase of text data and its challenges imply that DR… 
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