The Linear Estimation Problem and Information in Big-Data Systems
This paper addresses the problem of transforming the optimal linear estimation procedure in such a way that separate fragments of initial data are processed individually and concurrently. A representation of intermediate information is proposed that allows an algorithm to concurrently extract this information from each initial data set, combine it, and use it for estimation. It is shown that, on an information space constructed, an ordering is induced that reflects the concept of information quality.
The article defines the concept, structure and contents of the intellectual potential of society and specifies the limits of the information space in which various crimes infringe on this potential. It also outlines the range of the said crimes and describes ways to enhance the efficiency of criminal law to counteract them. The author emphasizes the role of university scholarship in augmenting the aforementioned potential and in the innovative development of economy, as well as in the protection of creative workers' rights and lawful interests.
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.
This proceedings publication is a compilation of selected contributions from the “Third International Conference on the Dynamics of Information Systems” which took place at the University of Florida, Gainesville, February 16–18, 2011. The purpose of this conference was to bring together scientists and engineers from industry, government, and academia in order to exchange new discoveries and results in a broad range of topics relevant to the theory and practice of dynamics of information systems. Dynamics of Information Systems: Mathematical Foundation presents state-of-the art research and is intended for graduate students and researchers interested in some of the most recent discoveries in information theory and dynamical systems. Scientists in other disciplines may also benefit from the applications of new developments to their own area of study.
Full texts of third international conference on data analytics are presented.
The author investigates issues related to the methodology and technology of applying the knowledge management system in an organization, describes infrastructure types needed to successfully practice a complex project of introducing an organizational, social and technological system of knowledge management.
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.
A form for an unbiased estimate of the coefficient of determination of a linear regression model is obtained. It is calculated by using a sample from a multivariate normal distribution. This estimate is proposed as an alternative criterion for a choice of regression factors.