G-Mail Spam Detection using Natural Language Processing
Abhishek Jain, Harsh Goel, Kireet Joshi, Vishan Kumar Gupta, Anurag Shukla, Paras Jain · 2023
Spam has gotten out of control and is now a serious problem that affects information security and user experience due to the exponential rise of email communication. Effective spam detection systems are essential to combating this issue. This study suggests a sophisticated method for Gmail spam detection that makes use of feature engineering and machine learning methods to improve the precision and dependability of email filtering. It significantly reduces user internet speed. Takes crucial information, such as user phone number. Identifying these spammers and the spam material can be a time-consuming and laborious process. Email spam is the practice of sending messages in mass via email. Because most of the expense of spam is borne by the recipient, it is essentially postage due advertising. Commercial advertising includes spam email. The model that is suggested may determine whether a message is spam or not by using Bayes’ theorem and the Naive Bayes’ Classifier.