Email Spams via Text Mining using Machine Learning Techniques
Tarika Verma1, Nasib Singh Gill2

1Ms. Tarika Verma, Research Scholar, Dept. of CS and Applications, M.D. University, Rohtak, India.
2Dr. Nasib Singh Gill, Professor, Dept. of CS & Applications, M. D. University, Rohtak, India.
Manuscript received on January 17, 2020. | Revised Manuscript received on January 22, 2020. | Manuscript published on February 10, 2020. | PP: 2535-2539 | Volume-9 Issue-4, February 2020. | Retrieval Number: D1915029420/2020©BEIESP | DOI: 10.35940/ijitee.D1915.029420
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Abstract: A lot of data is generated on daily basis which may potentially be useful. This data is generally unstructured and ambiguous to draw a meaning from it. High quality of information can be extracted from this potentially useful data typically through devising of patterns and trends in it. This is done using Text Mining which includes the initial parsing of the unstructured data, processing it and then leading to some meaningful and fascinating information hidden in it. This paper presents the machine learning techniques for text mining that are useful for spam detection in emails. 
Keywords: Text Mining, Machine Learning Techniques, Spam Mail Detection, ML Classifiers
Scope of the Article: Machine Learning