An Approach to Email Classification Using Bayesian Theorem

1
Denil Vira
Denil Vira
2
Dr. Denil Vira
Dr. Denil Vira
3
Pradeep Raja
Pradeep Raja
4
Shidharth Gada
Shidharth Gada
1 Mumbai University

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GJCST Volume 12 Issue C13

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An Approach to Email Classification Using Bayesian Theorem Banner
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Classifiers based on Bayesian theorem have been very effective in Spam filtering due to their strong categorization ability and high precision. This paper proposes an algorithm for email classification based on Bayesian theorem. The purpose is to automatically classify mails into predefined categories. The algorithm assigns an incoming mail to its appropriate category by checking its textual contents. The experimental results depict that the proposed algorithm is reasonable and effective method for email classification.

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References

  1. M Sahami,S Dumais,D Heckerman,E Horvitz (1998). A Bayesian approach to filtering junk email.
  2. I Androutsopoulos,G Paliouras,E Michelakis (2004). Learning to Filter Unsolicited Commercial E-Mail.
  3. I Androutsopoulos,J Koutsias,K Chandrinos,G Paliouras,C Spyropoulos (2000). An Evaluation of Naïve Bayesian Anti-Spam Filtering.
  4. Seongwook Youn,Dennis Mcleod (2007). Efficient Spam Email Filtering using Adaptive Ontology.
  5. Shlomo Hershkop,Salvatore Stolfo (2005). Combining email models for false positive reduction.
  6. Andrew Mccallum,Kamal Nigam (1998). A Comparison of Event Models for Naive Bayes Text Classification.
  7. Wenjia Wang,Phillis Jones,Derek Partridge (2000). Diversity between Neural Networks and Decision Trees for Building Multiple Classifier Systems.
  8. R Beckermann,A Mccallum,G Huang (2004). Automatic categorization of email into folders: benchmark experiments on Enron and SRI corpora.
  9. Fuchun Peng,Dale Schuurmans,Shaojun Wang (2004). Augmenting Naive Bayes Classifiers with Statistical Language Models.
  10. David Lewis,William Gale (1994). A sequential algorithm for training text classfiers.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

Denil Vira. 2012. \u201cAn Approach to Email Classification Using Bayesian Theorem\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 12 (GJCST Volume 12 Issue C13): .

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Issue Cover
GJCST Volume 12 Issue C13
Pg. 57- 60
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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September 6, 2012

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English

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Classifiers based on Bayesian theorem have been very effective in Spam filtering due to their strong categorization ability and high precision. This paper proposes an algorithm for email classification based on Bayesian theorem. The purpose is to automatically classify mails into predefined categories. The algorithm assigns an incoming mail to its appropriate category by checking its textual contents. The experimental results depict that the proposed algorithm is reasonable and effective method for email classification.

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An Approach to Email Classification Using Bayesian Theorem

Dr. Denil Vira
Dr. Denil Vira
Pradeep Raja
Pradeep Raja
Shidharth Gada
Shidharth Gada

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