關鍵字查詢 | 類別:研究報告 | | 關鍵字:運用資訊融合與模型融合發展穩定高效能之電子商務詐騙偵測架構

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序號 學年期 教師動態
1 106/1 資管系 張昭憲 副教授 研究報告 發佈 運用資訊融合與模型融合發展穩定高效能之電子商務詐騙偵測架構 , [106-1] :運用資訊融合與模型融合發展穩定高效能之電子商務詐騙偵測架構研究報告運用資訊融合與模型融合發展穩定高效能之電子商務詐騙偵測架構Developing Stable and High-Performance E-Commerce Fraud Detection Framework Based on Information Fusion and Model Fusion張昭憲模型融合;資訊融合;詐騙偵測;電子商務;巨量資料分析運用資訊融合與模型融合發展穩定高效能之電子商務詐騙偵測架構1. Ahmed M. (2016), Mahmood A. N., and Islam M. R., "A survey of anomaly detection techniques in financial domain," Future Generation Computer Systems 55 (2016) 278- 288. 2. Alford M. (2013), "Intelligent fraud detection: a comparison of neural and Bayesian methods," Computer Fraud & Security, pp. 14-16 3. Balazs, Jorge A., Juan D. Velásquez (2016), "Opinion Mining and Information Fusion: A survey," Volume 27, January 2016, Pages 95–110. 4. Carminati, M., et al. (2015), "BankSealer: A Decision support system for online banking fraud analysis and investigation," Computers & Security 53 (2015) 175-186. 5. Chang, W., and Chang, J. (2011), 'A Novel Two-Stage Phased Modeling Framework for Early Fraud Detection in Online Auctions', Expert System
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