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- W2912353108 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." @default.
- W2912353108 created "2019-02-21" @default.
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- W2912353108 date "2019-01-01" @default.
- W2912353108 modified "2023-10-17" @default.
- W2912353108 title "Spam User Detection Through Deceptive Images in Big Data" @default.
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- W2912353108 doi "https://doi.org/10.1007/978-3-319-99966-1_28" @default.
- W2912353108 hasPublicationYear "2019" @default.
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