Matches in SemOpenAlex for { <https://semopenalex.org/work/W3036211051> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W3036211051 abstract "Financial fraud is a growing problem with far-reaching concerns in the financial sector. Online transaction is the basic problem that raises many fraudulent quires around the world which cause loss of money to the people. These transactions generated huge volume of complex data in daily life. The depiction of fraud from credit card is still a key challenge due to two main reasons: firstly, profiles of ordinary and fraudulent behavior changes with the Passage of time, and secondly highly skewed credit card fraud records. Therefore, this study considered this challenge and proposed the solution to identify the fraudulent transactions through the credit cards using data mining techniques. Data mining has played a significant role in identifying credit card fraud from online transactions. Dataset collected from the publically available source and refine it. The employed classifiers are Naive Bayes, Bayes net, Logistic regression, Random forest, Decision tree, support vector machine, Decision stump, K- Nearest Neighbor, J48 and Binary Classification Technique. These techniques are applied on the preprocessed data. This data consists of 284,785 credit card transactions. Extensive experiments were conducted. The accuracy of each classifier was recorded in order to perform comparison. Our empirical analysis spotlights that K-NN outperforms in term of accuracy which is 99.95% than other classifiers. The findings of this study would be useful for the banking sector." @default.
- W3036211051 created "2020-06-25" @default.
- W3036211051 creator A5002173460 @default.
- W3036211051 creator A5013443131 @default.
- W3036211051 creator A5053176757 @default.
- W3036211051 creator A5068497484 @default.
- W3036211051 date "2020-01-01" @default.
- W3036211051 modified "2023-10-16" @default.
- W3036211051 title "Analysis of Variant Data Mining Methods for Depiction of Fraud" @default.
- W3036211051 cites W2342031101 @default.
- W3036211051 cites W2781512393 @default.
- W3036211051 cites W2795064858 @default.
- W3036211051 doi "https://doi.org/10.1007/978-3-030-49829-0_31" @default.
- W3036211051 hasPublicationYear "2020" @default.
- W3036211051 type Work @default.
- W3036211051 sameAs 3036211051 @default.
- W3036211051 citedByCount "4" @default.
- W3036211051 countsByYear W30362110512021 @default.
- W3036211051 countsByYear W30362110512022 @default.
- W3036211051 crossrefType "book-chapter" @default.
- W3036211051 hasAuthorship W3036211051A5002173460 @default.
- W3036211051 hasAuthorship W3036211051A5013443131 @default.
- W3036211051 hasAuthorship W3036211051A5053176757 @default.
- W3036211051 hasAuthorship W3036211051A5068497484 @default.
- W3036211051 hasConcept C119857082 @default.
- W3036211051 hasConcept C12267149 @default.
- W3036211051 hasConcept C124101348 @default.
- W3036211051 hasConcept C127722929 @default.
- W3036211051 hasConcept C136764020 @default.
- W3036211051 hasConcept C145097563 @default.
- W3036211051 hasConcept C151956035 @default.
- W3036211051 hasConcept C154945302 @default.
- W3036211051 hasConcept C169258074 @default.
- W3036211051 hasConcept C2780747020 @default.
- W3036211051 hasConcept C2983355114 @default.
- W3036211051 hasConcept C41008148 @default.
- W3036211051 hasConcept C52001869 @default.
- W3036211051 hasConcept C52003472 @default.
- W3036211051 hasConcept C75949130 @default.
- W3036211051 hasConcept C77088390 @default.
- W3036211051 hasConcept C84525736 @default.
- W3036211051 hasConceptScore W3036211051C119857082 @default.
- W3036211051 hasConceptScore W3036211051C12267149 @default.
- W3036211051 hasConceptScore W3036211051C124101348 @default.
- W3036211051 hasConceptScore W3036211051C127722929 @default.
- W3036211051 hasConceptScore W3036211051C136764020 @default.
- W3036211051 hasConceptScore W3036211051C145097563 @default.
- W3036211051 hasConceptScore W3036211051C151956035 @default.
- W3036211051 hasConceptScore W3036211051C154945302 @default.
- W3036211051 hasConceptScore W3036211051C169258074 @default.
- W3036211051 hasConceptScore W3036211051C2780747020 @default.
- W3036211051 hasConceptScore W3036211051C2983355114 @default.
- W3036211051 hasConceptScore W3036211051C41008148 @default.
- W3036211051 hasConceptScore W3036211051C52001869 @default.
- W3036211051 hasConceptScore W3036211051C52003472 @default.
- W3036211051 hasConceptScore W3036211051C75949130 @default.
- W3036211051 hasConceptScore W3036211051C77088390 @default.
- W3036211051 hasConceptScore W3036211051C84525736 @default.
- W3036211051 hasLocation W30362110511 @default.
- W3036211051 hasOpenAccess W3036211051 @default.
- W3036211051 hasPrimaryLocation W30362110511 @default.
- W3036211051 hasRelatedWork W10715555 @default.
- W3036211051 hasRelatedWork W12634471 @default.
- W3036211051 hasRelatedWork W4630997 @default.
- W3036211051 hasRelatedWork W621929 @default.
- W3036211051 hasRelatedWork W6310906 @default.
- W3036211051 hasRelatedWork W6552940 @default.
- W3036211051 hasRelatedWork W8167600 @default.
- W3036211051 hasRelatedWork W8948199 @default.
- W3036211051 hasRelatedWork W9481221 @default.
- W3036211051 hasRelatedWork W6520261 @default.
- W3036211051 isParatext "false" @default.
- W3036211051 isRetracted "false" @default.
- W3036211051 magId "3036211051" @default.
- W3036211051 workType "book-chapter" @default.