Sending and receiving SMS is very ordinary thing for any individual’s daily life. But when at the moment, we receive undesirable SMS frequently that waste our time and money as well and consequently this moment gives us unpleasant feeling. If undesirable messages are to be sent to a huge volume of recipients erratically have resulted in displeasure by consumers but gives large profit to spammers. There are lots of reasons like high internet speed, very cheap smart phones and user friendly interface of mobile web and mobile applications that attracts a huge volume of mobile phone users. These are the key factors expected to shape the future of the market. This paper focuses on SMS Spam filtering techniques and compared their performance. We compared the machine learning model’s performance and finally result indicates that the Logistic Regression model performed well with accuracy reaching up to 96.59%.
CITATION STYLE
Vishwakarma, A. K., Ansari, M. D., & Rai, G. (2021). SMS Spam Filtering Using Machine Learning Technique. In Lecture Notes in Electrical Engineering (Vol. 698, pp. 689–701). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-15-7961-5_66
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