Works matching IS 13895753 AND DT 2022 AND VI 22 AND IP 1
Results: 11
Study on early warning of E-commerce enterprise financial risk based on deep learning algorithm.
- Published in:
- Electronic Commerce Research, 2022, v. 22, n. 1, p. 21, doi. 10.1007/s10660-020-09454-9
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- Article
Correction to: Employing singular value decomposition and similarity criteria for alleviating cold start and sparse data in context-aware recommender systems.
- Published in:
- 2022
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- Publication type:
- Correction Notice
Optimal pricing decision of composite service offered by network providers in E-commerce environment.
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- Electronic Commerce Research, 2022, v. 22, n. 1, p. 177, doi. 10.1007/s10660-021-09487-8
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- Article
Rising stars prediction in reviewer network.
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- Electronic Commerce Research, 2022, v. 22, n. 1, p. 53, doi. 10.1007/s10660-021-09476-x
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- Article
Estimating user response rate using locality sensitive hashing in search marketing.
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- Electronic Commerce Research, 2022, v. 22, n. 1, p. 37, doi. 10.1007/s10660-021-09472-1
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- Article
Analyzing default risk among P2P platforms based on the LAS-STACK method by considering multidimensional signals under specific economic contexts.
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- Electronic Commerce Research, 2022, v. 22, n. 1, p. 77, doi. 10.1007/s10660-021-09505-9
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- Article
Cross-border e-commerce platform for commodity automatic pricing model based on deep learning.
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- Electronic Commerce Research, 2022, v. 22, n. 1, p. 1, doi. 10.1007/s10660-020-09449-6
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- Article
Estimating city-level poverty rate based on e-commerce data with machine learning.
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- Electronic Commerce Research, 2022, v. 22, n. 1, p. 195, doi. 10.1007/s10660-020-09424-1
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- Article
Dissecting click farming on the Taobao platform in China via PU learning and weighted logistic regression.
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- Electronic Commerce Research, 2022, v. 22, n. 1, p. 157, doi. 10.1007/s10660-020-09418-z
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- Article
Analyzing Bitcoin transaction fees using a queueing game model.
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- Electronic Commerce Research, 2022, v. 22, n. 1, p. 135, doi. 10.1007/s10660-020-09414-3
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- Article
Spam review detection using LSTM autoencoder: an unsupervised approach.
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- Electronic Commerce Research, 2022, v. 22, n. 1, p. 113, doi. 10.1007/s10660-020-09413-4
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- Publication type:
- Article