Naïve Bayes Filter for Communication & Enhancing Semantic in Email
Author(s) -
Mariyan Richard A,
Prasad Naik Hamsavath,
A Suhas,
G Drakshaveni
Publication year - 2020
Publication title -
international journal of recent technology and engineering (ijrte)
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.d4904.119420
Subject(s) - computer science , python (programming language) , naive bayes classifier , filter (signal processing) , bayes' theorem , world wide web , information retrieval , artificial intelligence , bayesian probability , support vector machine , computer vision , operating system
Due tothe current pandemic of COVID-19, the world has turned into ONLINE modeand an increase in online communication thereby information exchange, sharing useful data through emails and other social Medias. So addressing the security issues places a vital role in computer security and shouldhave thepriorities. We need a security check to enhance the inbox so that the important information or emails should not reach to the spam box. In this paper to improve the filtering techniques, wehave adopted the Naïve Bayes approach in implementation and enhancing the spam filter in the email. Bayes’s approach is efficient, accurate, and simple in implementing the proposed algorithm. Bayes algorithm is used to verify correct semantic information of the email and avoidsthe pass to pass approach if the incoming mail is important. The Python language is used to develop the proposed algorithm.
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