An Enhanced Cascading Model for E-Commerce Consumer Credit Default Prediction

Hou, Jun; Li, Qianmu; Liu, Yaozong; Zhang, Sainan

doi:10.4018/joeuc.20211101.oa13

Cited by 17 publications

(15 citation statements)

References 22 publications

(25 reference statements)

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“…In addition, as the consumer credit is at a relatively early stage in China and in order to quickly occupy market share and maintain an advantageous position, e-commerce companies have increased the annual growth rate of the total amount of credit and have lowered the conditions of credit through e-commerce. Aiming at the problem of e-commerce consumer credit default analysis, Hou et al [ 61 ] proposed a Fusion Enhanced Cascade Model (FECM). This model learns feature data of credit data by fusing multi-granularity modules and incorporates RF and Gradient-Boosted Decision Trees (GBDT) trade-off variance and bias methods.…”

Section: Resultsmentioning

confidence: 99%

Applications of Fusion Techniques in E-Commerce Environments: A Literature Review

Daskalakis¹,

Remoundou²,

Πεππές³

et al. 2022

Sensors

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The extreme rise of the Internet of Things and the increasing access of people to web applications have led to the expanding use of diverse e-commerce solutions, which was even more obvious during the COVID-19 pandemic. Large amounts of heterogeneous data from multiple sources reside in e-commerce environments and are often characterized by data source inaccuracy and unreliability. In this regard, various fusion techniques can play a crucial role in addressing such challenges and are extensively used in numerous e-commerce applications. This paper’s goal is to conduct an academic literature review of prominent fusion-based solutions that can assist in tackling the everyday challenges the e-commerce environments face as well as in their needs to make more accurate and better business decisions. For categorizing the solutions, a novel 4-fold categorization approach is introduced including product-related, economy-related, business-related, and consumer-related solutions, followed by relevant subcategorizations, based on the wide variety of challenges faced by e-commerce. Results from the 65 fusion-related solutions included in the paper show a great variety of different fusion applications, focusing on the fusion of already existing models and algorithms as well as the existence of a large number of different machine learning techniques focusing on the same e-commerce-related challenge.

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Section: Resultsmentioning

confidence: 99%

Applications of Fusion Techniques in E-Commerce Environments: A Literature Review

Daskalakis¹,

Remoundou²,

Πεππές³

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…There is a correlation between the support and the discrepancy of the evidence, as expressed in Eq (15).…”

Section: Plos Onementioning

confidence: 96%

“…Information fusion technology has solved many troubles [1][2][3][4][5][6][7] in the military, engineering, and environment since it developed in the 1970s [8]. The application have expanded to much more areas, such as extra energy, new materials, manufacturing, medicine, agriculture, transportation, and economy [9][10][11][12][13][14][15]. The utilization of information fusion technology enhances the system fault tolerance, self-adaptability, and reduces inference fuzziness.…”

Section: Introductionmentioning

confidence: 99%

Weighted assignment fusion algorithm of evidence conflict based on Euclidean distance and weighting strategy, and application in the wind turbine system

Gou

Zhang

et al. 2022

PLoS ONE

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In the process of intelligent system operation fault diagnosis and decision making, the multi-source, heterogeneous, complex, and fuzzy characteristics of information make the conflict, uncertainty, and validity problems appear in the process of information fusion, which has not been solved. In this study, we analyze the credibility and variation of conflict among evidence from the perspective of conflict credibility weight and propose an improved model of multi-source information fusion based on Dempster-Shafer theory (DST). From the perspectives of the weighting strategy and Euclidean distance strategy, we process the basic probability assignment (BPA) of evidence and assign the credible weight of conflict between evidence to achieve the extraction of credible conflicts and the adoption of credible conflicts in the process of evidence fusion. The improved algorithm weakens the problem of uncertainty and ambiguity caused by conflicts in the information fusion process, and reduces the impact of information complexity on analysis results. And it carries a practical application out with the fault diagnosis of wind turbine system to analyze the operation status of wind turbines in a wind farm to verify the effectiveness of the proposed algorithm. The result shows that under the conditions of improved distance metric evidence discrepancy and credible conflict quantification, the algorithm better shows the conflict and correlation among the evidence. It improves the accuracy of system operation reliability analysis, improves the utilization rate of wind energy resources, and has practical implication value.

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“…The other adopts the idea of a feature pyramid network (FPN) [ 16 ], where the prediction is performed after feature fusion. Based on the deep forest, a fusion-enhanced cascade model (FECM) is proposed, which fuses the surface features from the multigranularity module and combines the cascaded gradient descent tree (GBDT) and random forest models to fuse the features [ 17 ]. Zhang et al [ 18 ] proposed a train spatiotemporal graph convolutional network (TSTGCN) that includes two parts, spatiotemporal attention mechanism and spatiotemporal convolution.…”

Section: Related Workmentioning

confidence: 99%

Stance Detection Based on User Feature Fusion

Huang

Wang

Jin-yuan

et al. 2022

Computational Intelligence and Neuroscience

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Rapid development of the Internet has contributed to the widespread adoption of social network platforms. Network media plays an important role in the process of public opinion dissemination and bears significant social responsibility. Public opinion mining is of great significance for online media to improve the quality of content provision and enhance media credibility. How to make full use of user-generated content is the key to improving the accuracy of position detection tasks. In this paper, we proposed a stance detection model based on user feature fusion by using comments of netizens in false news events on Weibo as research content. The method of feature fusion is adopted to integrate vectors including user sentiment, cognitive features, and text feature at the feature layer for model training and position prediction. The model is evaluated on a dataset of related microblog comments in false news. The result shows that our proposed method has a certain improvement in the effect of stance detection.

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An Enhanced Cascading Model for E-Commerce Consumer Credit Default Prediction

Cited by 17 publications

References 22 publications

Applications of Fusion Techniques in E-Commerce Environments: A Literature Review

Applications of Fusion Techniques in E-Commerce Environments: A Literature Review

Weighted assignment fusion algorithm of evidence conflict based on Euclidean distance and weighting strategy, and application in the wind turbine system

Stance Detection Based on User Feature Fusion

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