Spam filtering using Association Rules and Naïve Bayes Classifier

Tianda Yang; Kai Qian; Dan Chia Tien Lo; Kamal Al Nasr; Ying Qian

doi:10.1109/PIC.2015.7489926

Spam filtering using Association Rules and Naïve Bayes Classifier

Tianda Yang, Kai Qian, Dan Chia Tien Lo, Kamal Al Nasr, Ying Qian

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Scopus citations

Abstract

E-mail service is one of the most popular Internet communication services. Thousands of companies, organizations and individuals use e-mail every day and get benefit from it. However, an amount of spam emails always hang around us and bring down our productivity. We urgently need a spam filtering to clean up our network environment. A spam filtering using Association Rule and Naïve Bayes Classifier is recommended here. Instead of focusing on increasing spam precision rate, we try to preserve all non-spam emails as the first priority. In the real world applications and services, that's what we should do. In this paper, we also provide the comparison between using both Association Rule and Naïve Bayes Classifier algorithms and just using Naïve Bayes Classifier.

Original language	English (US)
Title of host publication	Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015
Editors	Liang Xiao, Yinglin Wang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	638-642
Number of pages	5
ISBN (Electronic)	9781467380867
DOIs	https://doi.org/10.1109/PIC.2015.7489926
State	Published - Jun 10 2016
Externally published	Yes
Event	3rd IEEE International Conference on Progress in Informatics and Computing, PIC 2015 - Nanjing, China Duration: Dec 18 2015 → Dec 20 2015

Publication series

Name	Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015

Conference

Conference	3rd IEEE International Conference on Progress in Informatics and Computing, PIC 2015
Country/Territory	China
City	Nanjing
Period	12/18/15 → 12/20/15

Keywords

Apriori algorithm
Association Rule
Hadoop
Naïve Bayes Classifier
Spam
Spam filter

ASJC Scopus subject areas

Computer Science Applications
Computer Vision and Pattern Recognition
Information Systems

Access to Document

10.1109/PIC.2015.7489926

Cite this

Yang, T., Qian, K., Lo, D. C. T., Al Nasr, K., & Qian, Y. (2016). Spam filtering using Association Rules and Naïve Bayes Classifier. In L. Xiao, & Y. Wang (Eds.), Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015 (pp. 638-642). [7489926] (Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/PIC.2015.7489926

Spam filtering using Association Rules and Naïve Bayes Classifier. / Yang, Tianda; Qian, Kai; Lo, Dan Chia Tien et al.
Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015. ed. / Liang Xiao; Yinglin Wang. Institute of Electrical and Electronics Engineers Inc., 2016. p. 638-642 7489926 (Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Yang, T, Qian, K, Lo, DCT, Al Nasr, K & Qian, Y 2016, Spam filtering using Association Rules and Naïve Bayes Classifier. in L Xiao & Y Wang (eds), Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015., 7489926, Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015, Institute of Electrical and Electronics Engineers Inc., pp. 638-642, 3rd IEEE International Conference on Progress in Informatics and Computing, PIC 2015, Nanjing, China, 12/18/15. https://doi.org/10.1109/PIC.2015.7489926

Yang T, Qian K, Lo DCT, Al Nasr K, Qian Y. Spam filtering using Association Rules and Naïve Bayes Classifier. In Xiao L, Wang Y, editors, Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 638-642. 7489926. (Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015). doi: 10.1109/PIC.2015.7489926

Yang, Tianda ; Qian, Kai ; Lo, Dan Chia Tien et al. / Spam filtering using Association Rules and Naïve Bayes Classifier. Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015. editor / Liang Xiao ; Yinglin Wang. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 638-642 (Proceedings of 2015 IEEE International Conference on Progress in Informatics and Computing, PIC 2015).

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abstract = "E-mail service is one of the most popular Internet communication services. Thousands of companies, organizations and individuals use e-mail every day and get benefit from it. However, an amount of spam emails always hang around us and bring down our productivity. We urgently need a spam filtering to clean up our network environment. A spam filtering using Association Rule and Na{\"i}ve Bayes Classifier is recommended here. Instead of focusing on increasing spam precision rate, we try to preserve all non-spam emails as the first priority. In the real world applications and services, that's what we should do. In this paper, we also provide the comparison between using both Association Rule and Na{\"i}ve Bayes Classifier algorithms and just using Na{\"i}ve Bayes Classifier.",

keywords = "Apriori algorithm, Association Rule, Hadoop, Na{\"i}ve Bayes Classifier, Spam, Spam filter",

author = "Tianda Yang and Kai Qian and Lo, {Dan Chia Tien} and {Al Nasr}, Kamal and Ying Qian",

note = "Funding Information: The work is partially supported by the National Science Foundation under award: NSF proposal #1244697, #1438858, #124165l. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily retlect the views of the National Science Foundation. Publisher Copyright: {\textcopyright} 2015 IEEE.; 3rd IEEE International Conference on Progress in Informatics and Computing, PIC 2015 ; Conference date: 18-12-2015 Through 20-12-2015",

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N1 - Funding Information: The work is partially supported by the National Science Foundation under award: NSF proposal #1244697, #1438858, #124165l. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily retlect the views of the National Science Foundation. Publisher Copyright: © 2015 IEEE.

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N2 - E-mail service is one of the most popular Internet communication services. Thousands of companies, organizations and individuals use e-mail every day and get benefit from it. However, an amount of spam emails always hang around us and bring down our productivity. We urgently need a spam filtering to clean up our network environment. A spam filtering using Association Rule and Naïve Bayes Classifier is recommended here. Instead of focusing on increasing spam precision rate, we try to preserve all non-spam emails as the first priority. In the real world applications and services, that's what we should do. In this paper, we also provide the comparison between using both Association Rule and Naïve Bayes Classifier algorithms and just using Naïve Bayes Classifier.

AB - E-mail service is one of the most popular Internet communication services. Thousands of companies, organizations and individuals use e-mail every day and get benefit from it. However, an amount of spam emails always hang around us and bring down our productivity. We urgently need a spam filtering to clean up our network environment. A spam filtering using Association Rule and Naïve Bayes Classifier is recommended here. Instead of focusing on increasing spam precision rate, we try to preserve all non-spam emails as the first priority. In the real world applications and services, that's what we should do. In this paper, we also provide the comparison between using both Association Rule and Naïve Bayes Classifier algorithms and just using Naïve Bayes Classifier.

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Spam filtering using Association Rules and Naïve Bayes Classifier

Abstract

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Keywords

ASJC Scopus subject areas

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