基于数据跟踪与分类的资金数据流实时反馈系统

Ruizhu Xi, Bencai Gao, Xiao Xia
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引用次数: 0

摘要

数据分析和聚类技术已经成为分析复杂信息的最先进的方法。因此,本文研究了基于数据跟踪和分类的资金数据流实时反馈系统。现有的研究工作很少关注移动云中私有数据的安全删除问题,特别是移动云和移动终端产生的支付信息和敏感私信的安全删除问题,这些信息是不可恢复的,因此,通过优化数据跟踪框架和分类来实现模型。在建立模型后,本研究将其应用于资金数据流跟踪与监控中,并考虑实时性要求。该系统在不同的数据集上进行了测试,取得了令人信服的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time Feedback System of Funding Data Flow Based on Data Tracking and Classification
Data analysis and clustering technologies have becoming the state-of-the-art method of analyzing the complex information. Hence, this paper studies the real-time feedback system of the funding data flow based on the data tracking and classification. The existing research work pays little attention to the secure deletion of private data in mobile cloud, especially the secure deletion of payment information and sensitive private messages generated by mobile cloud and mobile terminal, which is not recoverable, hence, the model is implemented with the optimization of data tracking framework and the classification. After building the model, this research wrk applies it into the funding data flow tracking and monitoring, as well as considering the real-time requirement. The proposed system has been tested on various data sets and the convincing results are achieved.
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