Big Data Management and Analytics for Disability Datasets

Zhiwen Pan, Wen Ji, Yiqiang Chen, L. Dai, Jun Zhang
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引用次数: 1

Abstract

The disability datasets is the datasets which contains the information of disabled populations. By analyzing these datasets, professionals who work with disabled populations can have a better understanding of how to make working plans and policies, so that they support the populations in a better way. In this paper, we proposed a big data management and mining approach for disability datasets. The contributions of this paper are follows: 1) our proposed approach can improve the quality of disability data by estimating miss attribute values and detecting anomaly and low-quality data instances. 2) Our proposed approach can explore useful patterns which reflect the correlation, association and interactional between the disability data attributes. Experiments are conducted at the end to evaluate the performance of our approach.
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残疾数据集的大数据管理和分析
残障数据集是包含残障人群信息的数据集。通过分析这些数据集,从事残疾人工作的专业人员可以更好地了解如何制定工作计划和政策,从而更好地为残疾人提供支持。本文提出了一种残障数据集的大数据管理与挖掘方法。本文的贡献如下:1)该方法可以通过估计缺失属性值和检测异常和低质量数据实例来提高残疾数据的质量。2)我们提出的方法可以探索反映残疾数据属性之间的相关性、关联和交互作用的有用模式。最后进行了实验来评估我们的方法的性能。
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