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[目的/意义]大数据蕴藏着大知识和大情报,但呈现出价值密度低、分布不规律、价值隐藏深、变化频繁等特征,给数据挖掘工作带来巨大机遇与挑战,有必要探索新的挖掘方式。[方法/过程]以大数据环境下网络动态数据挖掘模式作为切入点,从数据生产方式、生产规模及技术成熟性等维度选择金融管理、新型互联网应用、移动互联网位置服务等应用领域,对其基本特征进行分析,最后以Facebook的动态数据挖掘分析平台为例进行系统说明。[结果/结论]提出应从体系结构、动态数据传输、系统接口、高可用技术及负载均衡等关键技术入手,对系统进行设计与优化。
[Purpose / Significance] Big data contains great knowledge and big intelligence, but presents features such as low value density, irregular distribution, hidden value and frequent changes, which bring great opportunities and challenges to data mining. It is necessary to explore new Way of digging [Method / Process] Taking the network dynamic data mining model in big data environment as the starting point, this paper selects the application fields of financial management, new internet application and mobile internet location service from the aspects of data production mode, production scale and technology maturity, Basic characteristics of the analysis, and finally to Facebook’s dynamic data mining analysis platform as an example for system description. [Result / Conclusion] It is proposed that the system should be designed and optimized from the key technologies of architecture, dynamic data transmission, system interface, high availability technology and load balancing.