Quantitative Detection of Financial Fraud Based on Deep Learning with Combination of E-Commerce Big Data
المؤلفون المشاركون
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-11، 11ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-12-24
دولة النشر
مصر
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
At present, there are more and more frauds in the financial field.
The detection and prevention of financial frauds are of great significance for regulating and maintaining a reasonable financial order.
Deep learning algorithms are widely used because of their high recognition rate, good robustness, and strong implementation.
Therefore, in the context of e-commerce big data, this paper proposes a quantitative detection algorithm for financial fraud based on deep learning.
First, the encoders are used to extract the features of the behaviour.
At the same time, in order to reduce the computational complexity, the feature extraction is restricted to the space-time volume of the dense trajectory.
Second, the neural network model is used to transform features into behavioural visual word representations, and feature fusion is performed using weighted correlation methods to improve feature classification capabilities.
Finally, sparse reconstruction errors are used to judge and detect financial fraud.
This method builds a deep neural network model with multiple hidden layers, learns the characteristic expression of the data, and fully depicts the rich internal information of the data, thereby improving the accuracy of financial fraud detection.
Experimental results show that this method can effectively learn the essential characteristics of the data, and significantly improve the detection rate of fraud detection algorithms.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liu, Jian& Gu, Xin& Shang, Chao. 2020. Quantitative Detection of Financial Fraud Based on Deep Learning with Combination of E-Commerce Big Data. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1143236
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liu, Jian…[et al.]. Quantitative Detection of Financial Fraud Based on Deep Learning with Combination of E-Commerce Big Data. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1143236
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liu, Jian& Gu, Xin& Shang, Chao. Quantitative Detection of Financial Fraud Based on Deep Learning with Combination of E-Commerce Big Data. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1143236
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1143236
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر