The Granular Differentiation Model of Rural Poverty Based on Data Mining

Abstract

Rural poverty is a hot topic around the world, and the precision of policy making become the key of China's poverty alleviation strategy in the new era. Based on the theory of information granularity in artificial intelligent domain, this study deeply analyzed the massive data from the targeted poverty alleviation big data platform by data mining, and then constructed a Granular poverty differentiation model to identify poverty differentiation characteristics at different levels of granularity in parts of China. We build a knowledge base to support the policy making of targeted poverty alleviation. This result can well support the research of China’s rural poverty.