РАЗРАБОТКА МАТЕМАТИЧЕСКОЙ МОДЕЛИ КЛАССИФИКАЦИИ ЭКСПЕРТНЫХ ЗНАНИЙ ПО АСТРОНОМИЧЕСКИМ НАБЛЮДЕНИЯМ
Everyone is talking about big data, and how it will transform go vernment. However, looking past the excitement, questions abound. How to use big data to make intelligent decisions? Perh aps most importantly, what value will it really deliver to the government and the citizenry it serves to? By reviewing the literatu re and summarizing insights from a series of business reports and interviews of public sector and top companies Chief Information Officers (CIOs), we offer a survey for both practitioners and researchers inter ested in understanding big data in the public sector of Russian Federation. Remarkable changes are taking place in IT industry of Russian Federati on at present: new strategies of Federal Government, sanctions and import substitution tendency. The paper makes the estimate of internal and external factors, which effect on big data development in public sector of Russian Federation and makes comparative analysis of Russian and world practices of the study area.
In this paper special data structure for big social graph storing and operating is presented. We discuss mainly graph paths searching, obtaining subgrapths and addition of new edges and vertices.
The compilation is based on the research of leading scientists in the field of system and software engineering as well as in the field of creation of information-analytical systems using Big Data technologies. The conference is devoted to the analysis of the state, the actual directions of development of scientific challenges to the practical results obtained by domestic and foreign scientists and experts in software engineering, as well as in the field of creation of information-analytical systems using Big Data technologies
Companies are increasingly paying close attention to the IP portfolio, which is a key competitive advantage, so patents and patent applications, as well as analysis and identification of future trends, become one of the important and strategic components of a business strategy. We argue that the problems of identifying and predicting trends or entities, as well as the search for technical features, can be solved with the help of easily accessible Big Data technologies, machine learning and predictive analytics, thereby offering an effective plan for development and progress. The purpose of this study is twofold, the first is an identification of technological trends, the second is an identification of application areas and/or that are most promising in terms of technology development and investment. The research was based on methods of clustering, processing of large text files and search queries in patent databases. The suggested approach is considered on the basis of experimental data in the field of moving connected UAVs and passive acoustic ecology control.