The work is dedicated to the analysis of criteria used to assess the effectiveness of public information systems to meet the demands of citizens for government services in the digital form. This work presents a methodology for assessing the priority of projects to create, maintain and upgrade government information systems. The groups of criteria based on qualitative and quantitative indicators are proposed, as well as a methodology that allows comparing information systems in order to identify unclaimed and ineffective government information systems. Qualitative criteria are determined by experts or as a result of surveys and quantitative criteria are statistical data. This paper proposes the use of machine learning methods to identify the relationship between qualitative indicators and metrics of information systems.
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