Computer Science ›› 2021, Vol. 48 ›› Issue (4): 85-90.doi: 10.11896/jsjkx.200500109
Special Issue: Big Data & Data Scinece
• Database & Big Data & Data Science • Previous Articles Next Articles
LI Si-di, GUO Bing-hui, YANG Xiao-bo
CLC Number:
[1]SHI C X,CHEN X J.The construction of P2P network lending personal credit evaluation index system[J].Journal of Changzhou University( Social Science Edition),2016,17(1):80-85. [2]LYU Z,ZHANG H.On the construction of personal credit information system under the background of big data[J].Compu-ter Programming Skills & Maintenance,2019(12):121-123. [3]BAI Y G,GUO B H,MI Z L,et al.Quantitative model of default risk for Internet financial platform[J].Computer Engineering,2018,44(12):108-114. [4]LIN G Q,ZHAO Y M,KUANG Q Z,et al.Predicting bad P2P loans with machine learning and complex network algorithm[J].Journal of Beijing Normal University(Natural Science),2017,53(1):24-27. [5]BA J L.The Research of the Network Characteristics of P2PLending and the Effect on Default Risk[D].Chengdu:School of Management and Economics,2019. [6]ZHANG L J,ZHAO K.Research on P2P Credit Personal Credit Evaluation Model Based on BP Neural Network[J].Electronic Technology & Software Engineering,2015(12):9-10. [7]JIANG R,YANG Z,FENG X X.Research on the Optimization of Credit Evaluation System of Science and Technology Enterprises—Based on GA-BP Neural Network Model[J].Credit Re-ference,2016,34(5):79-84. [8]WANG S Y.The research on credit risk assessment of P2P network loan based on fuzzy neural network[D].Changsha:Hunan University,2017. [9]BREIMAN L.Random forest[J].Machine Learning,2001,45:5-32. [10]LONG H M,ZOU H Z,ZHU J.Research on Credit Risk of Mobile Phone Stage Consumption Loan—An Empirical Analysis Based on RF-Logistic Model[J].The Theory and Practice of Finance and Economics,2019,40(5):27-33. [11]GORI M,MONFARDINI G,SCARSELLI F.A new model for learning in graph domains[C]//IEEE International Joint Conference on Neural Networks.2005. [12]PARK N,KAN A,DONG X L,et al.Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks[C]//the 25th ACM SIGKDD International Conference.2019. [13]BOJCHEVSKI A,SHCHUR O,ZÜGNER D,et al.Netgan:Generating graphs via random walks[J].arXiv:1803.00816,2018. [14]DINOI L,HAGENBUCHNER M,SCARSELLI F,et al.Webspam detection by probability mapping graphsoms and graph neural networks[C]//International Conference on Artificial Neural Networks.2010:372-381. [15]ADAMIC L A,ADAR E.Friends and neighbors on the web[J].Social Networks,2003,25:211-230. [16]DOROGOVTSEV S N,GOLTSEV A V,MENDES J F F.K-core percolation and k-core organization of complex networks[J].arXiv:cond-mat/0509102,2005. [17]BRIN S,PAGE L.The anatomy of a large-scale hypertextualweb search engine[C]//International Conference on World Wide Web.1998:107117. [18]BRUNA J,ZAREMBA W,SZLAM A,et al.Spectral networks and locally connected networks on graphs[J].arXiv:1312.6203v3,2013. [19]KIPF T N,WELLING M.Semi-supervised classification withgraph convolutional networks [J].arXiv:1609.02907v4,2016. |
[1] | LI Yong, WU Jing-peng, ZHANG Zhong-ying, ZHANG Qiang. Link Prediction for Node Featureless Networks Based on Faster Attention Mechanism [J]. Computer Science, 2022, 49(4): 43-48. |
|