Использование текст-майнинга в экономико-географическом отраслевом анализе целлюлозно-бумажной промышленности Европейской России
The authors show the need and some existing opportunities for analysis of non-traditional data sources to obtain a complete and more relevant picture of industries spatial development. The research methodology includes the use of text mining for economic and geographical studies. The relevance of the research is determined by insufficient completeness of official statistical data, cheapening of relevant information processing technologies and abundance of large text data sources in open access. The article discusses the role of the pulp and paper industry (as a key part of the timber industry) in economic and spatial development of modern Russia. The authors identify main trends in the economic and spatial development of the pulp and paper industry of European Russia, draw the conclusions on the expected industry trends and give recommendations for strategic management decisions to respond to industry challenges. The authors claim that the industry needs liberalization and stabilization, primarily through moratoriums on policy changes. The role of the use of big data, and in particular of text mining in economic and geographical research for reasonable and objective conclusions formation that can be used to make timely and balanced management decisions in the timber industry and the pulp and paper industry, is emphasized.
Russian Federation inherited a wide and well-developed timber harvesting infrastructure from the Soviet Union. It also inherited relatively strong timber processing industry, especially a network of giant pulp-and-paper plants with access to abundant water supply and cheap electricity. However, a number of factors deteriorate Russia's timber processing competitiveness. First, military security reasons made Soviet Union locate its processing industry, including timber processing, deep within the continent. Therefore, major Russian pulp-and-paper plants, as well as sawmills, panels and plywood plants face higher transportation costs when exporting their production than their counterparts in the United States and Finland. Second, major timber processing plants had been technologically advanced in time of deployment (1970-1980-s), but their technology and machinery has become quite backward over the decades, while investment in the production has nearly stopped altogether in 1990-s and was scarce in 2000-s.
This article defines the framework for identifying social and economic challenges that the timber industry currently faces in the regions of Northern European Russia. The analysis of identified problems on a regional and local scale for the case of Kostroma oblast is presented. The main institutional shifts during the
1990s–2000s are discussed, along with economic problems of regional timber industry systems and their social implications, as well as how companies and rural communities of Kostroma oblast have adapted to the challenges of the ongoing economic recession in 2009.
Pattern structures, an extension of FCA to data with complex descriptions, propose an alternative to conceptual scaling (binarization) by giving direct way to knowledge discovery in complex data such as logical formulas, graphs, strings, tuples of numerical intervals, etc. Whereas the approach to classification with pattern structures based on preceding generation of classifiers can lead to double exponent complexity, the combination of lazy evaluation with projection approximations of initial data, randomization and parallelization, results in reduction of algorithmic complexity to low degree polynomial, and thus is feasible for big data.
The proceedings of the 11th International Conference on Service-Oriented Computing (ICSOC 2013), held in Berlin, Germany, December 2–5, 2013, contain high-quality research papers that represent the latest results, ideas, and positions in the field of service-oriented computing. Since the first meeting more than ten years ago, ICSOC has grown to become the premier international forum for academics, industry researchers, and practitioners to share, report, and discuss their ground-breaking work. ICSOC 2013 continued along this tradition, in particular focusing on emerging trends at the intersection between service-oriented, cloud computing, and big data.
Full texts of third international conference on data analytics are presented.
In 2015-2016 the Department of Communication, Media and Design of the National Research University “Higher School of Economics” in collaboration with non-profit organization ROCIT conducted research aimed to construct the Index of Digital Literacy in Russian Regions. This research was the priority and remain unmatched for the momentIn 2015-2016 the Department of Communication, Media and Design of the National Research University “Higher School of Economics” in collaboration with non-profit organization ROCIT conducted research aimed to construct the Index of Digital Literacy in Russian Regions. This research was the priority and remain unmatched for the moment
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.
The article is dedicated to the analysis of Big Data perspective in jurisprudence. It is proved that Big Data have to be used as the explanatory and predictable tool. The author describes issues concerning Big Data application in legal research. The problems are technical (data access, technical imperfections, data verification) and informative (interpretation of data and correlations). It is concluded that there is the necessity to enhance Big Data investigations taking into account the abovementioned limits.
The rapidly increasing heterogeneous information volumes make it acute to generalize large amounts of data in order to be able to make strategically proper decisions. Information flows aggregation using traditional analytical tools is becoming difficult. As a result, a lot of new automated data analysis applications, including text-mining tools, are developing. The system of intellectual text data analysis iFORA, developed in ISSEK NRU HSE, is an example of such tool. iFORA capabilities are demonstrated on the beet sugar analysis case.
The collection contains articles by leading scientists and young professionals, dedicated to modern approaches to system research and mathematical modeling of economic, environmental, ecological and economic systems and the rational use of natural resources.
In Intergenerational Equity: Environmental and Cultural Concerns, the editors have produced an important, broad-based volume on intergenerational equity. The authors explore the principle of intergenerational equity in many dimensions, from the theoretical to the practical. While the primary focus is on intergenerational equity in the context of environmental resources and cultural heritage, the principle is also addressed in a broad array of other contexts. The final section of the volume considers intergenerational justice as it applies to indigenous peoples, genocide, migration, sovereign wealth funds and foreign investment. The chapters also provide a critical analysis of the issues and a consideration of the difficulties in implementing intergenerational equity.
Effective management of scientific and technological advancement of Russian agricultural production requires the anticipating monitoring of the existing informational and analytic media in the top-priority spheres of the agriculture. Increasing necessity in the calculation and application of objective and reliable analytical data for the strategic decision making at different levels is forcing the integration of applied analytical tools into analytical systems. These tools are versatile and primarily based on the automatic data processing. The analytical system of text mining is presented as an example of intellectual data analysis and its opportunities
Aquaculture is nowadays one of the fastest growing sectors of the economy. In Russia, however, the volume of aquaculture production is low due to several factors. At the same time, the key regulatory documents of the Federal level pay great attention to the fishery industry, ambitious goals to increase production and exports are set. The implementation of aquaculture development programs should be based, among other things, on the introduction of new technologies, the development of scientific and technological potential and the adaptation of the experience of foreign countries. Planning the development of any industry in the modern world should be comprehensive and systematic, and determining promising technological solutions and management practices requires contemporary and accurate analytical tools. This article proposes the use of strategic analytics as a conceptual approach to the data analysis in terms of their current volume and diversification level. It is proposed to use the iFora big data mining system developed by the HSE as a tool for analysing promising trends in the development of the aquaculture industry. The article proposes the use of semantic analysis of large amounts of textual information as the main method. The proposed methodology will be used in the analysis of the aquaculture industry in subsequent publications.
The New Russian Encyclopedia is a fundamental reference publication in 18 volumes that characterizes nature, population, economy, history, science, art, technology and other important aspects. Contains about 60,000 articles, about 30,000 biographies, about 15,000 color illustrations, maps, charts, diagrams, tables. Leaves since 2003.