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- W2888258349 abstract "Nowadays, Big Data is commonly used in many business sectors. Its use is also relevant for the construction industry. One of the most promising areas of Big Data technologies application is their use for risk analysis and assessment. Big Data represents an efficient way to manage modern risks by analyzing the unlimited amount of structured and unstructured information. The study examines principles of operational risks classification in construction companies on the basis of Big Data technologies. The final goal of such classification is the creation of a solution pattern for subsequent use of Big Data. As an example, a solution pattern for such business problem as Construction: Detection of Insurance Fraud is created. Application of the Big Data analytics for fraud detection has a series of advantages as compared to traditional approaches. Insurance companies can build systems that include all relevant data sources. An analysis of operational risks by means of self-organizing Kohonen maps on the basis of the Deductor analytical platform is performed." @default.
- W2888258349 created "2018-08-31" @default.
- W2888258349 creator A5005000422 @default.
- W2888258349 date "2018-01-01" @default.
- W2888258349 modified "2023-09-23" @default.
- W2888258349 title "Classification of operational risks in construction companies on the basis of big data" @default.
- W2888258349 doi "https://doi.org/10.1051/matecconf/201819305072" @default.
- W2888258349 hasPublicationYear "2018" @default.
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