Research on Key Information Processing Technology of Environmental Law Enforcement Based on Big Data

Abstract

In the enforcement of environmental cases, the acquisition of key information such as plots and evidence has always been a key difficulty. However, the traditional search engine-based key information processing technology for environmental law enforcement suffers from long-term defects and high information loss rate due to the excessive reliance on manpower. In this regard, based on big data technology, this paper proposes new key information processing methods for environmental law enforcement. Specifically, it uses a combination of data warehouse and agent software to initially store the production information of the law enforcement objects; then generates metadata according to the specific requirements of environmental law enforcement; and then classifies the relevant metadata through the K-NN classifier; Finally, the BP neural network algorithm is used to aggregate the classified data to form effective plots and evidence. In order to verify the feasibility of this technology, this paper designs a comparison experiment with its traditional method. The experimental results show that the key information processing technology of environmental law enforcement based on big data has faster information acquisition rate and lower information loss rate, which is a feasible new approach.