Application of Machine Learning Methods for Filling and Updating Nuclear Knowledge Databases

Working prototypes of the scalable semantic web portals, which are deployed on cloud platforms and intended for use in universities educational activity, are discussed. The first project is related to teaching in the field of nuclear physics and nuclear power engineering. The second project is related to training in computer science and programming. The possibility of using the DL-Learner software in conjunction with the Apache Jena Reasoners in order to refine the ontologies that are designed on the basis of the SROIQ(D) description logic is shown. A software agent for the context-sensitive searching for new knowledge in the WWW has been developed as a toolkit for ontologies enrichment. The binary Pareto relation and Levenshtein metrics are used in order to evaluate the measure of compliance of the found content concerning a specific domain. It allows the knowledge engineer to calculate the measure of the proximity of an arbitrary network resource about classes and objects of specific knowledge graphs. The suggested software solutions are based on cloud computing using DBaaS and PaaS service models to ensure the scalability of data warehouses and network services. Examples of applying the software and technologies under discuss are given.