Journal of Physics: Conference Series 1168, pp. 032133.
ISSN/ISBN: Not available at this time. DOI: 10.1088/1742-6596/1168/3/032133
Abstract: In the era of big data, data is growing explosively. Data quality control has become a key factor in maximizing data value. It is important and urgent to establish a scientific data quality detection method. Benford's law has become an effective tool for detection of data quality and identification of anomaly data in various fields. On the basis of expounding the basic principles of Benford's law, this paper summarizes its application in different levels of natural and social sciences, explores the data conditions of the law and the factors affecting the accuracy of the detection, and proposes the model improvement idea in three aspects of extending detection scope, combination of several methods and strengthening the explanation of detection results. The development of Benford's Law in the future requires scholars from all fields to study more about its essence, strengthen its integration with other data processing technologies, and then expand its application.
Bibtex:
@article{,
doi = {10.1088/1742-6596/1168/3/032133},
url = {https://doi.org/10.1088%2F1742-6596%2F1168%2F3%2F032133},
year = 2019,
month = {feb},
publisher = {{IOP} Publishing},
volume = {1168},
pages = {032133},
author = {Feifei Li and Shuqing Han and Hongyv Zhang and Jiaojiao Ding and Jianhua Zhang and Jianzhai Wu},
title = {Application of Benford's law in Data Analysis},
journal = {Journal of Physics: Conference Series},
}
Reference Type: Journal Article
Subject Area(s): Accounting, Computer Science