RETRACTED: A Smart Social Insurance Big Data Analytics Framework Based on Machine Learning Algorithms

Abstract

Social insurance is an individual’s protection against risks such as retirement, death or disability. Big data mining and analytics are a way that could help the insurers and the actuaries to get the optimal decision for the insured individuals. Dependently, this paper proposes a novel analytic framework for Egyptian Social insurance big data. NOSI’s data contains data, which need some pre-processing methods after extraction like replacing missing values, standardization and outlier/extreme data. The paper also presents using some mining methods, such as clustering and classification algorithms on the Egyptian social insurance dataset through an experiment. In clustering, we used K-means clustering and the result showed a silhouette score 0.138 with two clusters in the dataset features. In classification, we used the Support Vector Machine (SVM) classifier and classification results showed a high accuracy percentage of 94%.

Keywords

• social insurance
• data integration
• big data mining and big data analytics