Abstract
In the current years, we’ve seen a sensational addition within the volume of spam email. Other connected types of spam are increasingly uncovering as an issue of significance, extraordinarily the spam on Instant electronic messaging administrations, and Short Message Service (SMS) or portable spam. Like email spam, the SMS spam issue is drawn nearer with lawful, monetary or specialized measures. Among the extensive variety of specialized measures. There are two types of messages, first one is wanted messages from those people whom we know and other is unsolicited or unwanted messages, these unsolicited messages are called spams. Over the last 1.5 decade it has become a very big problem. Every day a very huge amount of spam messages is received by the users. This paper introduces an approach to classify the messages into spam/legitimate categories using the Rapid miner tool. In this Paper we have used Stop-word Removal in initial stages to filter spam of a Spam SMS Dataset on the basis of Content Based Filtering Technique. Then after getting the desired result that is when we have filtered the Messages. After that we have applied Nave-Bayes Classification with the Help of Rapid-Miner Tool which will help us in getting the desired out-come that is These messages will get categorized into Spam (bad) messages and Ham (Good) messages. This paper endeavors to order the predominant famous procedures for arranging messages as spam or ham and recommend the possible techniques
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Ahuja, L. (2018). Handling Web Spamming Using Logic Approach. In: Singh, M., Gupta, P., Tyagi, V., Flusser, J., Ören, T. (eds) Advances in Computing and Data Sciences. ICACDS 2018. Communications in Computer and Information Science, vol 906. Springer, Singapore. https://doi.org/10.1007/978-981-13-1813-9_38
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DOI: https://doi.org/10.1007/978-981-13-1813-9_38
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