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.
- Mcdermott S, Turk M A. What are the implications of the big data paradigm shift for disability and health?{J}. Disability & Health Journal, 2015, 8(3): 303--304.Google Scholar
- Marijn Janssen, Haiko van der Voort, Agung Wahyudi. Factors influencing big data decision-making quality. Journal of Business Research, 2017, 70: 338--345.Google ScholarCross Ref
- Hoffman S. Big Data and the Americans with Disabilities Act. Social Science Electronic Publishing, 2017, 68(4):777--793. http://www.acm.org/class/howtouse.htmlGoogle Scholar
- Mckinley S, Levine M. Cubic Spline Interpolation, Methods Of Shape-Preserving Spline Approximation. 2007: 37--59.Google Scholar
- Ma M X, Ngan H Y T, Liu W. Density-based Outlier Detection by Local Outlier Factor on Largescale Traffic Data. Electronic Imaging, 2016.Google Scholar
- Wold S, Esbensen K, Geladi P. Principal component analysis. Chemometrics & Intelligent Laboratory Systems, 1987, 2(1): 37--52.Google ScholarCross Ref
- Borgelt C. An Implementation of the FP-growth Algorithm, In Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations. ACM, 2005: 1--5. Google ScholarDigital Library
- William W. Cohen: Fast effective rule induction. in ICML 1995: 115--123. Google ScholarDigital Library
- Olive D J. Linear Regression Analysis. Technometrics, 2013, 45(4):362--363.Google Scholar
- Longadge R, Dongre S. Class imbalance problem in data mining review. arXiv preprint arXiv:1305.1707, 2013.Google Scholar
- I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci. 2002. Wireless Sensor Networks: A Survey. Comm. ACM 38, 4, 2002, 393--422. Google ScholarDigital Library
Index Terms
- Big Data Management and Analytics for Disability Datasets
Recommendations
Comprehensive Data Management and Analytics for General Society Survey Dataset
ICCSE'19: Proceedings of the 4th International Conference on Crowd Science and EngineeringThe General Society Survey(GSS) is a kind of government-funded survey which aims at examining the Socio-economic status, quality of life, and structure of contemporary society. GSS dataset is regarded as one of the authoritative source for the ...
Multimedia Big Data Analytics: A Survey
With the proliferation of online services and mobile technologies, the world has stepped into a multimedia big data era. A vast amount of research work has been done in the multimedia area, targeting different aspects of big data analytics, such as the ...
Big Data Management: Advanced Issues and Approaches
The objective of this article is to provide the advanced issues and approaches of big data management. The literature review indicates the overview of big data management; the aspects of Big Data Analytics BDA; the importance of big data management; the ...
Comments