Analyze the Relationship Between Regional Poverty Rate and Education Level Based on Big Data
- 10.2991/978-94-6463-034-3_90How to use a DOI?
- Big Data; Data Analysis; Regional Poverty; Education Level
In recent years, with the advent of the era of big data, China has achieved achievements that other countries cannot achieve in a short period of time in terms of GROSS national product, government fiscal revenue and national budget expenditure. However, poverty cannot be completely eliminated in a short period of time. There are still some people in the stage of poverty in the society, which affects the educational level of their children. The analysis of the relationship between regional poverty and educational level plays a very important role in the targeted deployment of educational resources by the state. Therefore, based on big data analysis technology, this paper conducts an in-depth study on the relationship between regional poverty interest rate and education level. In this paper, the Apriori algorithm of data mining algorithm is used to build a correlation model between poverty rate and education level, and gradually discover frequent project sets by increasing the number of elements in the project set. This article through the questionnaire survey method for the analysis of the data, after analyzing the data by using the model can be concluded that the education level and economic levels were positively correlated, the higher economic level, the higher the level of education, therefore, to conclude, to the poor areas should increase the investment of education resources, efforts to improve education popularity, realize the well-off society.
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Cite this article
TY - CONF AU - Tianai Yue PY - 2022 DA - 2022/12/23 TI - Analyze the Relationship Between Regional Poverty Rate and Education Level Based on Big Data BT - Proceedings of the 2022 3rd International Conference on Big Data and Informatization Education (ICBDIE 2022) PB - Atlantis Press SP - 875 EP - 883 SN - 2589-4900 UR - https://doi.org/10.2991/978-94-6463-034-3_90 DO - 10.2991/978-94-6463-034-3_90 ID - Yue2022 ER -