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A Practical Approach for Emails Multiclass Classification according to Senders using Naïve Bayers Technique

by G. Girija Rani, M. Indra Sena Reddy
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 144 - Number 6
Year of Publication: 2016
Authors: G. Girija Rani, M. Indra Sena Reddy
10.5120/ijca2016910399

G. Girija Rani, M. Indra Sena Reddy . A Practical Approach for Emails Multiclass Classification according to Senders using Naïve Bayers Technique. International Journal of Computer Applications. 144, 6 ( Jun 2016), 34-37. DOI=10.5120/ijca2016910399

@article{ 10.5120/ijca2016910399,
author = { G. Girija Rani, M. Indra Sena Reddy },
title = { A Practical Approach for Emails Multiclass Classification according to Senders using Naïve Bayers Technique },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2016 },
volume = { 144 },
number = { 6 },
month = { Jun },
year = { 2016 },
issn = { 0975-8887 },
pages = { 34-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume144/number6/25186-2016910399/ },
doi = { 10.5120/ijca2016910399 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:46:56.608177+05:30
%A G. Girija Rani
%A M. Indra Sena Reddy
%T A Practical Approach for Emails Multiclass Classification according to Senders using Naïve Bayers Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 144
%N 6
%P 34-37
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Emails are parts of everyday life. These messages have become increasingly important and widespread method of communication because of its time speed, where the amount of email messages received per day can range from tens for a regular user to thousands for companies. Everyone is overwhelmed with emails, including relational (structured) and non-relational (semi-structured or non-structured), quite a bit of which is repetitive, stale and of drastically differing quality. This large quantity is confounded. Not just spam messages are thought to be 'garbage', additionally undesirable messages (e.g. advertisements, lottery) individuals’ waste a lot of time unknowingly by surfing them. So there is much need to categorization of Emails. Classification can help to meet lawful and administrative necessities for recovering particular data inside of a set time span, and this is frequently the inspiration driving implementing data classification. This paper aims at examining on ways doing supervised and unsupervised grouping of messages as per email content.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Supervised unsupervised classification.

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