摘要：Social insurance is an individual’s protection against risks such asretirement, death or disability. Big data mining and analytics are a way that couldhelp the insurers and the actuaries to get the optimal decision for the insuredindividuals. Dependently, this paper proposes a novel analytic framework forEgyptian Social insurance big data. NOSI’s data contains data, which need somepre-processing methods after extraction like replacing missing values,standardization and outlier/extreme data. The paper also presents using some miningmethods, such as clustering and classification algorithms on the Egyptian socialinsurance dataset through an experiment. In clustering, we used K-means clusteringand the result showed a silhouette score 0.138 with two clusters in the datasetfeatures. In classification, we used the Support Vector Machine (SVM) classifier andclassification results showed a high accuracy percentage of 94%.
关键词：Social Insurance; Data Integration; Big Data Mining ; Big Data Analytics
