GRDB:用于嘈杂信息网络的声明性和交互式分析的系统

W. E. Moustafa, Hui Miao, A. Deshpande, L. Getoor
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引用次数: 5

摘要

人们对各种类型网络(包括生物、物理、社会和科学合作网络)的数据分析方法越来越感兴趣。通常,描述这些网络的数据是观测到的,因此有噪声和不完整;对于有意义的数据分析,它通常处于错误的保真度和抽象级别。这个演示展示了GrDB,这个系统使数据分析人员能够编写声明性程序来指定和组合不同的网络数据清理任务,可视化输出,并在必要时参与决策审查和纠正过程。GrDB的声明性接口使得快速编写分析任务并在数据上执行它们变得非常容易,而可视化组件有助于调试程序并执行细粒度更正。
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GRDB: a system for declarative and interactive analysis of noisy information networks
There is a growing interest in methods for analyzing data describing networks of all types, including biological, physical, social, and scientific collaboration networks. Typically the data describing these networks is observational, and thus noisy and incomplete; it is often at the wrong level of fidelity and abstraction for meaningful data analysis. This demonstration presents GrDB, a system that enables data analysts to write declarative programs to specify and combine different network data cleaning tasks, visualize the output, and engage in the process of decision review and correction if necessary. The declarative interface of GrDB makes it very easy to quickly write analysis tasks and execute them over data, while the visual component facilitates debugging the program and performing fine grained corrections.
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