Research On Spam Filter Based On Improved Naive Bayes and KNN Algorithm
- 10.2991/icmmct-16.2016.220How to use a DOI?
- spam filter, Naive Bayes, KNN.
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.
- © 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/).
Cite this article
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 -