Research On Spam Filter Based On Improved Naive Bayes and KNN Algorithm

DOI

10.2991/icmmct-16.2016.220How to use a DOI?

Keywords

spam filter, Naive Bayes, KNN.

Abstract

In the field of data mining and pattern recognition, classification is a very important core technology. This paper present two kinds of improved classification algorithm. Using the improved Naive Bayes (NB) and KNN algorithm structure classifier to filter normal mail and spam. Improved NB algorithm can dynamically adjust the threshold k, reduces the mail mistake rate. Center vector method is introduced into the similarity calculation formula of KNN, better reflect the interrelation between the text and categories. Finally, improved NB algorithm and KNN algorithm make comparison and analysis, it is concluded that the effective experimental results.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Biyi Ren
AU  - Yuliang Shi
PY  - 2016/03
DA  - 2016/03
TI  - Research On Spam Filter Based On Improved Naive Bayes and KNN Algorithm
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Computing Technology
PB  - Atlantis Press
SP  - 1112
EP  - 1115
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-16.2016.220
DO  - 10.2991/icmmct-16.2016.220
ID  - Ren2016/03
ER  -