@inproceedings{2b16c9d5f91e4b86be6183a1f5d9a2d8,
title = "Analysis and comparison of fax Spam detection algorithms",
abstract = "Spam detection is one of the important problems in these days. Many spam detection methods were proposed, but fax spam detection is not popular. It not easy to directly use existing content-based spam detection methods for fax documents because the documents are processed as image rather than text. In this paper, we propose a fax spam detection framework which is based on keyword patterns by using an Optical Character Recognition (OCR) technique. To demonstrate how effective the proposed framework is, we analyze and compare three fax spam detection algorithms (rule based method, SVM based method, and na{\"i}ve Bayesian based method) with 219 normal and 212 spam documents. Our recommendation is to use na{\"i}ve Bayesian based method which is capable of achieving an accuracy of 92.49\%.",
keywords = "Comparison, Detection, Fax spam, Na{\"i}ve Bayesian, Rule based filtering, SVM",
author = "Jaekwang Kim and Hyoungshick Kim and Lee, \{Jee Hyong\}",
note = "Publisher Copyright: {\textcopyright} 2017 ACM.; 11th International Conference on Ubiquitous Information Management and Communication, IMCOM 2017 ; Conference date: 05-01-2017 Through 07-01-2017",
year = "2017",
month = jan,
day = "5",
doi = "10.1145/3022227.3022284",
language = "English",
series = "Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication, IMCOM 2017",
publisher = "Association for Computing Machinery, Inc",
booktitle = "Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication, IMCOM 2017",
}