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Spam Detection Approach Using Modified Pre-processing With NLP

Neelam Choudhary1 , Nitesh Dubey2

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-10 , Page no. 158-161, May-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7si10.158161

Online published on May 05, 2019

Copyright © Neelam Choudhary, Nitesh Dubey . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Neelam Choudhary, Nitesh Dubey, “Spam Detection Approach Using Modified Pre-processing With NLP,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.10, pp.158-161, 2019.

MLA Style Citation: Neelam Choudhary, Nitesh Dubey "Spam Detection Approach Using Modified Pre-processing With NLP." International Journal of Computer Sciences and Engineering 07.10 (2019): 158-161.

APA Style Citation: Neelam Choudhary, Nitesh Dubey, (2019). Spam Detection Approach Using Modified Pre-processing With NLP. International Journal of Computer Sciences and Engineering, 07(10), 158-161.

BibTex Style Citation:
@article{Choudhary_2019,
author = {Neelam Choudhary, Nitesh Dubey},
title = {Spam Detection Approach Using Modified Pre-processing With NLP},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2019},
volume = {07},
Issue = {10},
month = {5},
year = {2019},
issn = {2347-2693},
pages = {158-161},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=994},
doi = {https://doi.org/10.26438/ijcse/v7i10.158161}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i10.158161}
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=994
TI - Spam Detection Approach Using Modified Pre-processing With NLP
T2 - International Journal of Computer Sciences and Engineering
AU - Neelam Choudhary, Nitesh Dubey
PY - 2019
DA - 2019/05/05
PB - IJCSE, Indore, INDIA
SP - 158-161
IS - 10
VL - 07
SN - 2347-2693
ER -

           

Abstract

However, the growth in emails has also led to an unprecedented increase in the number of illegitimate mail, or spam 49.7% of emails sent is spam - because current spam detection methods lack an accurate spam classifier. We are excited by the decline in the volume of email spam but it also raises the question as to whether the email spam business is dying and will continue to decline. Besides the volume change, we also consider the quality of email spam and the impact, which may constitute a new trend of email spam business. For instance, spammers may post email spam in a more complicated way using spoofed email addresses and changing email relay servers. That kind of email spam may slip away under the inspection of spam filters. Thus, it motivated us to investigate the evolution of email spam using advanced techniques such as topic modelling and network analysis. We try to find out the real trend of email spam business through email content, meta information such as headers, and sender-to-receiver network over a long period of time.

Key-Words / Index Term

Spam detection, email, NLP, spam classification

References

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