Research Article
Application of Data Mining Technology in Poverty Alleviation Prediction in Ethnic Areas
@INPROCEEDINGS{10.4108/eai.23-2-2024.2345877, author={Fei Feng}, title={Application of Data Mining Technology in Poverty Alleviation Prediction in Ethnic Areas}, proceedings={Proceedings of the 4th International Conference on Informatization Economic Development and Management, IEDM 2024, February 23--25, 2024, Kuala Lumpur, Malaysia}, publisher={EAI}, proceedings_a={IEDM}, year={2024}, month={5}, keywords={data mining big data poverty alleviation}, doi={10.4108/eai.23-2-2024.2345877} }
- Fei Feng
Year: 2024
Application of Data Mining Technology in Poverty Alleviation Prediction in Ethnic Areas
IEDM
EAI
DOI: 10.4108/eai.23-2-2024.2345877
Abstract
In order to understand the application of poverty alleviation prediction in ethnic areas, an application research based on data mining technology in poverty alleviation prediction in ethnic areas is put forward. Firstly, this paper analyzes that the wide application of big data technology has opened the curtain of a new era, promoted profound changes in all walks of life, and made China society step into an information economy society, which has become an important driving force for China's economic transformation. Secondly, it briefly describes the methods in the prediction of poverty alleviation in ethnic areas, and uses the resources of big data to provide fast, convenient and efficient services to the society and people through various platforms such as the Internet, local area network and government network, so as to realize the resource utilization of big data. Finally, it is summarized that big data platforms such as "precise poverty alleviation cloud", "e-commerce cloud", "smart agriculture Internet of Things cloud", "education cloud" and "medical health cloud" should be developed and applied. The big data platform is helpful to change the thinking and path of poverty alleviation and promote the healthy, intelligent and sustainable development of rural society in ethnic areas.