Spam Text Detection

Authors

  • Dharmik Timbadia  Computer Engineering, Rajiv Gandhi Institute of Technology, Mumbai, Maharashtra, India
  • Niraj Vesaokar  Computer Engineering, Rajiv Gandhi Institute of Technology, Mumbai, Maharashtra, India

DOI:

https://doi.org//10.32628/CSEIT2173151

Keywords:

Spam Detection, unsolicited commercial email, SMS, NLP

Abstract

Spam Detection is the process to classify text which contains irrelevant or unsolicited messages sent over the internet, typically to a large number of users, for the purposes of advertising, phishing, spreading malware, etc. Text summarization is the technique of converting long text to short. The intention is to make a coherent and fluent summary having only the most points outlined within the document. A USA based machine learning expert which had 13 years of experience and currently teaches people his skills, states his technique has proved to be critical in quickly and accurately summarizing voluminous texts, something which might be expensive and time-consuming if avoided machines. Machine learning models are usually trained to know documents and distil the useful information before outputting the specified summarized texts.

References

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Published

2021-06-30

Issue

Section

Research Articles

How to Cite

[1]
Dharmik Timbadia, Niraj Vesaokar, " Spam Text Detection, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 7, Issue 3, pp.698-704, May-June-2021. Available at doi : https://doi.org/10.32628/CSEIT2173151