Autor: |
Cheng WANG, Pengfei SHU |
Jazyk: |
čínština |
Rok vydání: |
2019 |
Předmět: |
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Zdroj: |
大数据, Vol 5, Pp 2019052-1 (2019) |
Druh dokumentu: |
article |
ISSN: |
2096-0271 |
DOI: |
10.11959/j.issn.2096-0271.2019052 |
Popis: |
Internet lending fraud prediction method based on association graph limits the mining efficiency and depth of features,as well as the reusability and expressibility of features.To solve this problem,the network embedding technology was introduced,and the structure and semantic information in the network by using the vector was expressed.The network update method based on periodic time window and decision batch method were proposed to improve the performance of network embedding in the two business requirements of accuracy and real-time.The experiment shows that the network embedding technology can automatically and effectively learn the implicit relationship and characteristics of the network.By combining the traditional method and the network embedding method,the fraud prediction performance has been significantly improved. |
Databáze: |
Directory of Open Access Journals |
Externí odkaz: |
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