Naive Bayes spam filtering using word-position-based attributes and length-sensitive classification thresholds

@inproceedings{Hovold2005NaiveBS,
  title={Naive Bayes spam filtering using word-position-based attributes and length-sensitive classification thresholds},
  author={Johan Hovold},
  booktitle={NODALIDA},
  year={2005}
}
This paper explores the use of the naive Bayes classifier as the basis for personalised spam filters. Several machine learning algorithms, including variants of naive Bayes, have previously been used for this purpose, but the author’s implementation using word-position-based attribute vectors gave very good results when tested on several publicly available corpora. The effects of various forms of attribute selection – removal of frequent and infrequent words, respectively, and by using mutual… CONTINUE READING
Highly Cited
This paper has 46 citations. REVIEW CITATIONS
31 Citations
5 References
Similar Papers

Citations

Publications citing this paper.

Similar Papers

Loading similar papers…