An Efficient Framework for Spam Mail Detection in Attachments using NLP

Amol Malge, Dr. S. M. Chaware

Abstract: now a days mail becomes a vital medium for communication as it offers a lot of advantage over SMS service. But spams also known as junks are immerged as hurdle for the email service. Spam attracting more attention as internet fields are widely affected due to such unwanted spams. Recently conducted study shows that 70 % of todays business mails are spams. Therefore many serious problems such as wasting storage space, growing volume of spams etc. are immerged. The main motto behind such spams is to damage financially to the company and individual. Hence number of approaches had been proposed to protect systems from such unwanted spams, and filtering is one of them. Proposed approach is working on the Gmail host ids where it identifies the spam Emails by detecting signature of the Email with the support of the strong NLP protocols.

Keywords: Correlation, Ontology, NLP, inverted index, hardness

How to Cite?: Amol Malge, Dr. S. M. Chaware, "An Efficient Framework for Spam Mail Detection in Attachments using NLP", Volume 5 Issue 6, June 2016, International Journal of Science and Research (IJSR), Pages: 1121-1125, https://www.ijsr.net/getabstract.php?paperid=11061603, DOI: https://dx.doi.org/10.21275/11061603