학술논문

A Novel Method for Mining Abnormal Behaviors in Social Medical Insurance
Document Type
Conference
Source
2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) Information Technology, Electronics and Mobile Communication Conference (IEMCON), 2018 IEEE 9th Annual. :744-748 Nov, 2018
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Fields, Waves and Electromagnetics
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Insurance
Data mining
Hospitals
Industries
Transaction databases
data mining
frequent itemset
medical insurance management
fraud detection
fund management
behavioral patterns
Language
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.