Email Surveillance Using Non-negative Matrix Factorization

@article{Berry2005EmailSU,
  title={Email Surveillance Using Non-negative Matrix Factorization},
  author={Michael W. Berry and Murray Browne},
  journal={Computational & Mathematical Organization Theory},
  year={2005},
  volume={11},
  pages={249-264}
}
In this study, we apply a non-negative matrix factorization approach for the extraction and detection of concepts or topics from electronic mail messages. For the publicly released Enron electronic mail collection, we encode sparse term-by-message matrices and use a low rank non-negative matrix factorization algorithm to preserve natural data non-negativity and avoid subtractive basis vector and encoding interactions present in techniques such as principal component analysis. Results in topic… CONTINUE READING

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