Content-Based Anti Spam Detection Using ML and NLP |
Author(s): |
| Prayag Gavshinde , Acropolis Institute of Technology and Research Indore; Raghav Agrawal, Acropolis Institute of Technology and Research Indore; Rishi Somani , Acropolis Institute of Technology and Research Indore; Sambhav Jain, Acropolis Institute of Technology and Research Indore; Dr. Asif Ali, Acropolis Institute of Technology and Research Indore |
Keywords: |
| Text Classification, NLP, Machine Learning, Deep Learning |
Abstract |
|
Spam filtering is a widely discussed and studied topic In the field of pattern classification. Emails, SMS as well social media comments can be filtered as spam and not spam based on many features like frequency or occurrence of few words than content, the length of the e-mail, SMS, or the domain from which it is being sent. Based on these basic characteristics, researchers have come up with many techniques to identify content as spam and non-spam content. In this project, we aim to implement and evaluate three major e-mail spam filtering algorithms. They are, Naïve Bayes method, k-Nearest Neighbors, and Support Vector Machines. |
Other Details |
|
Paper ID: IJSRDV8I100105 Published in: Volume : 8, Issue : 10 Publication Date: 01/01/2021 Page(s): 190-193 |
Article Preview |
|
|
|
|
