Hybrid data cleaning method for project monitoring based on an integrated quality index and the analytic hierarchy process

The aim of this study is to develop a novel data cleaning method for project monitoring that enables data quality assessment prior to loading into information systems. The approach is based on methods of system analysis, semantic text analysis, robust statistics, and the Analytic Hierarchy Process. A data cleaning model based on an integrated quality index (IQI) is proposed, combining syntactic, semantic, and logical criteria. The developed algorithm calculates the IQI and supports informed decision-making regarding data acceptance. Experimental results demonstrate a significant increase in defect detection recall while maintaining high precision, enabling the identification of hidden errors and effective application of the proposed approach in data pre-cleaning systems.

Authors: D. L. Tukeev, O. V. Afanasieva, I. M. Novozhilov, E. A. Prokina, O. S. Volgina

Direction: Informatics, Computer Technologies And Control

Keywords: data cleaning, data quality, project monitoring, integrated quality index, analytic hierarchy process, semantic analysis, anomaly detection

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