Anomaly data management and big data analytics: an application on disability datasets

International Journal of Crowd Science

article

Zhiwen Pan¹  Wen Ji¹  Yiqiang Chen¹  Lianjun Dai²  Jun Zhang³ 

[1] Institute of Computing Technology Chinese Academy of Sciences , Beijing, China;Information Centre of China Disabled Persons’ Federation, Beijing, China;Information Centre of China Disabled Persons’ Federation, Beijing, China ...Show all authors

关键词: Decision support systems;    Data analytics;    anomaly data detection;    Data management systems;   

DOI  :  10.1108/IJCS-09-2018-0020

学科分类：内科医学

来源: Emerald Publishing

【 摘 要 】

Purpose The disability datasets are the datasets that contain the information of disabled populations. By analyzing these datasets, professionals who work with disabled populations can have a better understanding of the inherent characteristics of the disabled populations, so that working plans and policies, which can effectively help the disabled populations, can be made accordingly. Design/methodology/approach In this paper, the authors proposed a big data management and analytic approach for disability datasets. Findings By using a set of data mining algorithms, the proposed approach can provide the following services. The data management scheme in the approach can improve the quality of disability data by estimating miss attribute values and detecting anomaly and low-quality data instances. The data mining scheme in the approach can explore useful patterns which reflect the correlation, association and interactional between the disability data attributes. Experiments based on real-world dataset are conducted at the end to prove the effectiveness of the approach. Originality/value The proposed approach can enable data-driven decision-making for professionals who work with disabled populations.

【 授权许可】

CC BY