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http://dx.doi.org/10.7471/ikeee.2019.23.4.1393

A Method for Spam Message Filtering Based on Lifelong Machine Learning  

Ahn, Yeon-Sun (Dept. of Software, Gachon University)
Jeong, Ok-Ran (Dept. of Software, Gachon University)
Publication Information
Journal of IKEEE / v.23, no.4, 2019 , pp. 1393-1399 More about this Journal
Abstract
With the rapid growth of the Internet, millions of indiscriminate advertising SMS are sent every day because of the convenience of sending and receiving data. Although we still use methods to block spam words manually, we have been actively researching how to filter spam in a various ways as machine learning emerged. However, spam words and patterns are constantly changing to avoid being filtered, so existing machine learning mechanisms cannot detect or adapt to new words and patterns. Recently, the concept of Lifelong Learning emerged to overcome these limitations, using existing knowledge to keep learning new knowledge continuously. In this paper, we propose a method of spam filtering system using ensemble techniques of naive bayesian which is most commonly used in document classification and LLML(Lifelong Machine Learning). We validate the performance of lifelong learning by applying the model ELLA and the Naive Bayes most commonly used in existing spam filters.
Keywords
Spam Filtering; Naive Bayes Classifier; Lifelong Machine Learning; ELLA;
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