Answers are grounded in this paper and cite their sources.
Millions of people use email correspondence for communication across the globe and it is a critically vital application for many businesses. Considerable amount of unsolicited mail flows into user's mail boxes on a daily basis. A major negative aspect since the past decade has been bulk spam or phishing mail. Besides such unsolicited spam emails being wearisome for many email users, it also puts pressure on the IT infrastructure of organizations and costs businesses billions of dollars in lost efficiency. Increasing need of effectively filtering spam has become vital. We thus use BPNN filtering algorithm i.e. Artificial Neural Network Feed forward with Back Propagation, which is based on text classification to classify significant emails from unsolicited ones.
No takes yet. Share an insight, caveat, or question.
Tuteja et al. (2016) studied this question.
Synapse has enriched one closely related paper. Consider it for comparative context: