Algorithms and soft for adapting the knowledge base of project management information systems

The effectiveness of design solutions largely depends on the promptness of processing a large amount of data from various sources, which determines the feasibility of using information decision support systems (IDSS) in the field of project management. The peculiarities of information processes in project management greatly complicate or even make it impossible to implement in practice methods for constructing analytical, as well as probabilistic and statistical dependencies between the characteristics of the modeled project management system and the indicators of its internal and external environment. In this regard, as an algorithmic support for IDSS for project management, it is promising to use precedent methods for analyzing information based on knowledge about similar situations previously observed in the practice of project management, and representing knowledge in the form of ontologies. Analysis of practical situations in the field of project management makes it possible to substantiate the expediency of organizing a monitoring procedure for the IDSS knowledge base, based on the results of which decisions on its adaptation are made. The article proposes the main ways of this adaptation: changing the structure and basic elements (first of all, concepts) of ontologies; clarification of the structure of the description of current situations and, therefore, precedents. The developed algorithm for monitoring the IDSS knowledge base on project management for the analysis and identification of typical situations of the feasibility of changing it is described. The algorithm is distinguished by the possibility of developing recommendations on the modification of ontologies based on a fuzzy classification of search results and using precedents relevant to current situations. A procedure is proposed for changing the structure of the description of precedents, taking into account the results of assessing the indices of the fuzzy correspondence of the characteristics of the existing precedents to the characteristics of the project being implemented. A description of a computer program that implements the proposed algorithm and its components, as well as the results of its application are given.