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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM33527

Email Spam Filtering System using Machine Learning

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM33527

Volume:

8 |

6 |

Jun 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM33527

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

NR

N. Renuka

ARR

A. Revanth Reddy

SRA

Shaik Rezwan Ali

LRG

L. Rishitha Goud

TRR

T. Rishitha Reddy

PCMP

Prof. C M Preethi

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Abstract

This project involves building an email management system using machine learning. It will sort emails into categories, help users organize their emails, and handle emails in multiple languages. For email classification, it will use the Naive Bayes algorithm. User feedback will be used to personalize the filtering process. Separate models will be developed for English and Hindi using Natural Language Processing (NLP). To handle infrequent login attempts, the system will detect emails containing login information. The project will focus on data collection, model evaluation, security, and scalability. A user-friendly interface will be designed, and advanced techniques like sentiment analysis and improved Hindi NLP will be explored.Flags emails containing login information of frequent logged in information of the user.This system can greatly improve how users manage their emails by addressing key problems and offering a versatile and dependable solution.

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Cite This Article

N. Renuka, A. Revanth Reddy, Shaik Rezwan Ali, L. Rishitha Goud, T. Rishitha Reddy, Prof. C M Preethi, "Email Spam Filtering System using Machine Learning," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 6, Jun 2024. https://doi.org/10.55041/IJSREM33527

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Publication Date

6/19/2024

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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The authors declare no conflict of interest related to this research work.

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