Publication: A review of feature extraction optimization in SMS spam messages classification
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Date
2016
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Verlag
Abstract
Spam these days has become a definite nuisance to mobile users. Provision of Short Messages Services (SMS) has been intruded, in line with an advancement of mobile technology by the emergence of SMS spam. This issue has not only cause distressing situation but also other serious threats such as money loss, fraud, and false news. The focus of this study is to excavate the features extraction in classifying SMS spam messages at users� end. Its objective is to study the discriminatory control of the features and considering its informative or influence factor in classifying SMS spam messages. This study has been conducted by gathering research papers and journals from numerous sources on the subject of spam classification. The discovery offers a motivational effort for further execution in a wider perspective of combating spam such as measurement of spam�s risk level. � Springer Nature Singapore Pte Ltd. 2016.
Description
Keywords
Feature extraction review, SMS spam, Spam classification, Spam feature extraction, Spam filtering, Extraction, Feature extraction, Internet, Risk assessment, Soft computing, Extraction optimizations, Features extraction, Mobile Technology, Research papers, Short message, Spam classification, Spam filtering, Spam messages, Classification (of information)