A Systematic Review on Spam Filtering Techniques based on Natural Language Processing Framework

Humans are referred to be as the sharpest species on the Earth. The capability to impart and share knowledge makes individual most sharp of all. They turned out to be brilliant to the point that they created up certain computer languages. The online networking stages so forth avails in sharing data, conveying yet accompanies downside additionally. The paramount downside is Spamming and Digital tormenting. Spams are the undesirable messages that entice the clients, goes through our data transmission and compromise our privacy. Spams are immerged as obstruction for email administrations. Around 70% of business mails are Spam. The Principle point is to identify the Spams and remove them which incorporates offensiveness, deceives to other sites, inappropriate content, vulgarity and those not specific with content by means of Natural Language Processing. Natural language processing is abridged as NLP, is an application of Artificial Intelligence. Subsequently, different methodologies have been proposed to manage undesirable Spams and Spam filtering is one of them. Various methods have been proposed by the researchers to deal with Spams. The implementation text classification techniques like tokenizing, stemming, POS-tagging and chunking took part in it.