Abstract:
This paper presents a novel approach to knowledge extraction from large-scale datasets using a neural network when applied to the real-world problem of payment card fraud...Show MoreMetadata
Abstract:
This paper presents a novel approach to knowledge extraction from large-scale datasets using a neural network when applied to the real-world problem of payment card fraud detection. Fraud is a serious and long term threat to a peaceful and democratic society. We present SOAR (Sparse Oracle-based Adaptive Rule) extraction, a practical approach to process large datasets and extract key generalizing rules that are comprehensible using a trained neural network as an oracle to locate key decision boundaries. Experimental results indicate a high level of rule comprehensibility with an acceptable level of accuracy can be achieved. The SOAR extraction outperformed the best decision tree induction method and produced over 10 times fewer rules aiding comprehensibility. Moreover, the extracted rules discovered fraud facts of key interest to industry fraud analysts.
Date of Conference: 18-23 July 2010
Date Added to IEEE Xplore: 14 October 2010
ISBN Information:
ISSN Information:
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- IEEE Keywords
- Index Terms
- Learning Rule ,
- Credit Card ,
- Knowledge Extraction ,
- Neural Network ,
- Decision Tree ,
- Inductive Reasoning ,
- Real-world Problems ,
- Decision Boundary ,
- Fraud Detection ,
- Acceptable Level Of Accuracy ,
- Payment Card ,
- Business ,
- Support Vector Machine ,
- Natural Populations ,
- Black Box ,
- Performance Metrics ,
- Related Data ,
- Small Datasets ,
- Neural Model ,
- Support Vector Machine Classifier ,
- Sparse Datasets ,
- Multilayer Perceptron ,
- Set Of Rules ,
- False Positive Ratio ,
- Deep Structure ,
- Transaction Data ,
- Confusion Matrix ,
- Drug Trafficking ,
- Training Examples
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Learning Rule ,
- Credit Card ,
- Knowledge Extraction ,
- Neural Network ,
- Decision Tree ,
- Inductive Reasoning ,
- Real-world Problems ,
- Decision Boundary ,
- Fraud Detection ,
- Acceptable Level Of Accuracy ,
- Payment Card ,
- Business ,
- Support Vector Machine ,
- Natural Populations ,
- Black Box ,
- Performance Metrics ,
- Related Data ,
- Small Datasets ,
- Neural Model ,
- Support Vector Machine Classifier ,
- Sparse Datasets ,
- Multilayer Perceptron ,
- Set Of Rules ,
- False Positive Ratio ,
- Deep Structure ,
- Transaction Data ,
- Confusion Matrix ,
- Drug Trafficking ,
- Training Examples