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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: March 2026
Volume 11 | Issue 3
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 118
Article Submitted : 21462
Article Published : 8501
Total Authors : 22357
Total Reviewer : 805
Total Countries : 157
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| Paper Title: | ENHANCED DETECTION OF ANAMOLY ACTIVITIES IN CREDIT CARD SYSTEMS USING SUPERVISED MACHINE LEARNING TECHNIQUES |
| Authors Name: | P.Senthil , Porselvi.C , Deepa.A , Elakkiya.S |
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IJRTI_181450
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| Published Paper Id: | IJRTI2103040 |
| Published In: | Volume 6 Issue 3, March-2021 |
| DOI: | |
| Abstract: | Web based business is the most useful answer for grow the client base and accomplish the biggest stage with a tiny speculation. The quick development in the E-Commerce has drastically expanded Mastercards use for online buys and it initiated explode in the Visa misrepresentation. For both online just as normal buy Visa turned into the most well known method of installment, misrepresentation cases associated with it are likewise emerging. The false exchanges are mistaken for authentic exchanges and the basic example coordinating with strategies are not frequently enough to distinguish those fakes precisely. Proficient misrepresentation location framework execution got basic for all Visa giving banks to limit their misfortunes. Current methods dependent on Artificial Intelligence, Data mining, Fuzzy rationale, Machine learning, Sequence Alignment, Genetic Programming and so forth, are advanced in recognizing different Mastercard deceitful exchanges. These methodologies surely lead to a productive Visa extortion recognition framework. This task presents a study of different strategies utilized in Mastercard misrepresentation discovery instruments and assesses every philosophy dependent on certain plan standards |
| Keywords: | Credit Card, Anomaly Detection, Machine Learning, Hidden Markov Model. |
| Cite Article: | "ENHANCED DETECTION OF ANAMOLY ACTIVITIES IN CREDIT CARD SYSTEMS USING SUPERVISED MACHINE LEARNING TECHNIQUES ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.6, Issue 3, page no.195 - 201, March-2021, Available :http://www.ijrti.org/papers/IJRTI2103040.pdf |
| Downloads: | 000205248 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2103040
Registration ID:181450
Published In: Volume 6 Issue 3, March-2021
DOI (Digital Object Identifier):
Page No: 195 - 201 Country: redhills,chennai , Tamil Nadu, India Research Area: Engineering Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2103040 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2103040 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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