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Spam User Detection Through Deceptive Images in Big Data

  • Shareena Zafar
  • Nawal Irum
  • Sidra Arshad
  • Tahir NawazEmail author
Chapter
Part of the EAI/Springer Innovations in Communication and Computing book series (EAISICC)

Abstract

Image mining has a very emerging sub-domain, namely, web image mining, and researchers are warmly excited towards it. This study presents a deep detail of former studies and ideas that we come up with, i.e. what is Image Mining and what are Web Image Mining techniques. In the domain of web image mining, this study also proposes an idea to recognize and cope with the deceptive images found on the web. It further helps in banning the fraudulent and annoying web users along with solutions in enhancing the users’ behavior in social networking websites like Facebook, Twitter, Tumbler, etc., in blogs, and in e-shopping websites like eBay, Amazon, Daraz.pk, Kaymu.pk, etc. Apart from this, the study also mentions nearly of the conceivable future directions for the researchers in aforementioned domain.

Keywords

Image mining Spam detection Feature extraction Web image mining Pattern matching Image recognition Web content mining 

Notes

Acknowledgments

This work is dedicated to our parents who are the reason for us being at this point in our studies and to teachers/advisors who made our basic concepts clear enough for our efforts to be put in such a presentable form. We thank them both for encouraging us toward the research in this domain.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Shareena Zafar
    • 1
  • Nawal Irum
    • 1
  • Sidra Arshad
    • 1
  • Tahir Nawaz
    • 1
    Email author
  1. 1.Department of Computer ScienceUniversity of Lahore (Sargodha Campus)SargodhaPakistan

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