Big Data and Machine Learning in Government Projects: Expert Evaluation Case

In this paper, we present the Expert Hub System, which was designed to help governmental structures find the best experts in different areas of expertise for better reviewing of the incoming grant proposals. In order to define the areas of expertise with topic modeling and clustering, and then to relate experts to corresponding areas of expertise and rank them according to their proficiency in certain areas of expertise, the Expert Hub approach uses the data from the Directorate of Science and Technology Programmes. Furthermore, the paper discusses the use of Big Data and Machine Learning in the Russian government project

Efficient Algorithms for Constructing Multiplex Networks Embedding

Network embedding has become a very promising techniquein analysis of complex networks. It is a method to project nodes of anetwork into a low-dimensional vector space while retaining the structureof the network based on vector similarity. There are many methods ofnetwork embedding developed for traditional single layer networks. Onthe other hand, multilayer networks can provide more information aboutrelationships between nodes. In this paper, we present our random walkbased multilayer network embedding and compare it with single layerand multilayer network embeddings. For this purpose, we used severalclassic datasets usually used in network embedding experiments and alsocollected our own dataset of papers and authors indexed in Scopus

Efficient Algorithms for Constructing Multiplex Networks Embedding

Network embedding has become a very promising techniquein analysis of complex networks. It is a method to project nodes of anetwork into a low-dimensional vector space while retaining the structureof the network based on vector similarity. There are many methods ofnetwork embedding developed for traditional single layer networks. Onthe other hand, multilayer networks can provide more information aboutrelationships between nodes. In this paper, we present our random walkbased multilayer network embedding and compare it with single layerand multilayer network embeddings. For this purpose, we used severalclassic datasets usually used in network embedding experiments and alsocollected our own dataset of papers and authors indexed in Scopus

Big Data and Machine Learning in Government Projects: Expert Evaluation Case

In this paper, we present the Expert Hub System, which was designed to help governmental structures find the best experts in different areas of expertise for better reviewing of the incoming grant proposals. In order to define the areas of expertise with topic modeling and clustering, and then to relate experts to corresponding areas of expertise and rank them according to their proficiency in certain areas of expertise, the Expert Hub approach uses the data from the Directorate of Science and Technology Programmes. Furthermore, the paper discusses the use of Big Data and Machine Learning in the Russian government project

Tendencies and perspectives of sports industry development

The article reveals the trends and prospects for the development of the sport industry, which has a global character. The authors defined the sport industry. It was stated that the presence of accessible and qualitative sport infrastructure is the most important condition for the development of the valuable market for sport services, advance of the industry of sport. The conducted studies have shown that in the modern world, there is a constant search for new effective forms and types of commercial activities in the system of physical culture and sports. The relevance of the study lies in the fact that basis of analysis of the development trends of the global and emerging national sport industry. Study has drawn the main conclusions and recommendations for its further development. The article points out the imperfection of statistics and the lack of monitoring of these indicators. The taxation schemes for manufacturers of sport goods and services and the principles of financing sport education need to be revised. Training entrepreneurial personnel taking into account of specific character and development of the market relations of the branch of sport properly still is not conducted, and this complicates the solution of the problem. It is necessary to streamline the regulatory framework, to ensure the preparation of educational standards and requirements for training personnel for the entrepreneurial structures of the industry, by taking into account the peculiarities of the development of the modern sphere of sports and all levels of its management.</jats:p