Подход к построению прогностической модели жизненного цикла информационных ресурсов на базе стохастических gert-сетей и технологии processmining

Abstract

The article proposes an approach to predicting the numerical parameters of the life cycle of information resources. The main task of this work is to develop a tool for numerical forecasting of the life cycle of information resources based on actual life cycle data in the form of resource history event logs. The forecast is carried out using the apparatus of stochastic GERT networks. The construction of the GERT model is performed using the Process Mining algorithmic apparatus and the ProM software framework. The object of the analysis was the data of the Scientific Electronic Library Online. The data is publicly available on the Kaggle.com website. To build a GERT network describing the life cycle model of an information resource, we used the methods of intellectual analysis of Process Mining processes implemented using the ProM Framework. In the course of the work, an analysis of the life cycle of information resources of the Scientific Electronic Online Library was carried out. The paper presents the process of extracting data used to model a GERT network using the ProM framework. The data obtained made it possible to restore the topology of the stochastic network and identify the laws of probability density distribution of the duration of the life cycle stages. On the basis of the constructed GERT-network, the law of distribution of the probability density of the duration of the life cycle of an information resource was described. The obtained result confirms the applicability of Process Mining technology to probabilistic analysis and forecasting of the life cycle of information resources.