A Novel Method for Mining Abnormal Behaviors in Social Medical Insurance

Abstract

It is very important to strengthen the management of medical insurance and guarantee the steady operation of medical insurance fund. Data mining technology can provide an effective solution for medical aggregation behavior mining. It is helpful to find out the people who have the gathering behavior of medical treatment. In view of the aggregation behavior of medical insurance funds during operation, this study proposes the consistent behavior mining algorithm based on frequent pattern mining. Experiments show that this algorithm has better performance than Apriori and Eclat, can effectively detect the aggregation behavior of medical insurance, and has achieved remarkable results in the management and supervision of medical insurance.