Risk Assessment Model of Accounting Resource Sharing Management Based on Big Data Association Rule Algorithm

With the rapid development of the Internet, information technologys and cloud computing, today’s society has entered the era of big data (BD). Information technology is promoting the transformation of BD to another technology that subverts the IT industry. Whether it is mobile, e-commerce, or the Internet of things, sites generate huge amounts of different types of data every day. In the research content of group law extraction, how to extract the defined knowledge or rules hidden in this BD with different characteristics, mixed with a large amount of noise. Since risk-based resource management analysis is not the best value in the world, the evaluation results are incomplete, and the evaluation cycle is long. This paper presents a risk assessment model for accounting resource sharing management based on a BD association rule algorithm. On this basis, the optimal statistical parameters are used to formulate risk assessment rules and determine risk factors to determine the risk assessment of statistical source distribution based on the BD algorithm rules. It can be seen from the test results that when the data reaches 10 million level, the paper algorithm is about six times faster than the traditional algorithm, so the BD association rule algorithm is a superior choice for accounting resource sharing management.