Abstract
Email has become a significant correspondence medium. Official, personal, social and promotional and other messages hit our mail box every day. From the research, it has discovered that the normal office specialist gets 121 messages for every day. Now and then because of flooding of messages in inbox, a portion of the some mails stay unattended, so on the off chance that messages are characterized into top need folders, at that point, the issue of unattended or unanswered mail will be tackled. In this paper, we identified the key features of email classification are temporal, behavioral, single email multinomial valued, content and local and global features. Also datasets, techniques and tools in various email classification like spam, phishing, multifolder and machine generated email classification were studied. Different email classifiers provide different mechanisms for classification. Challenges in email classification are discussed. From the study, it is found that J48 classification algorithm works the best for spam and ham email classification. In comparison with various email service provider, Microsoft Outlook filters the mail based on many criteria.
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Shroff, N., Sinhgala, A. (2021). Email Classification Techniques—A Review. In: Kotecha, K., Piuri, V., Shah, H., Patel, R. (eds) Data Science and Intelligent Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 52. Springer, Singapore. https://doi.org/10.1007/978-981-15-4474-3_21
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DOI: https://doi.org/10.1007/978-981-15-4474-3_21
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