Проблемы математической истории: Основания, информационные ресурсы, анализ данных
This book constitutes the refereed proceedings of the 10th International Conference on Formal Concept Analysis, ICFCA 2012, held in Leuven, Belgium in May 2012. The 20 revised full papers presented together with 6 invited talks were carefully reviewed and selected from 68 submissions. The topics covered in this volume range from recent advances in machine learning and data mining; mining terrorist networks and revealing criminals; concept-based process mining; to scalability issues in FCA and rough sets.
This paper examines the data from federal surveys of small enterprises. It outlines the methodology and the main stages in the development of the program for survey of innovation and analyzes the innovation activity of small enterprises. The paper also includes suggestions to update the current survey instruments and develop new methods of measurement of research and development results, their implementation in the production processes and transfer to the real economy.
This book constitutes the second part of the refereed proceedings of the 10th International Conference on Formal Concept Analysis, ICFCA 2012, held in Leuven, Belgium in May 2012. The topics covered in this volume range from recent advances in machine learning and data mining; mining terrorist networks and revealing criminals; concept-based process mining; to scalability issues in FCA and rough sets.
Computers have already entered all the spheres of human activity including the process of teaching and studying. Although computers will never take the place of the teacher, they are important and helpful assistants. The use of the computers is a methodical device applied in the modern approaches of teaching of any subject. But will the expenses of the computers and software be covered?
We address the external effects on public sector efficiency measures acquired using Data Envelopment Analysis. We use the health care system in Russian regions in 2011 to evaluate modern approaches to accounting for external effects. We propose a promising method of correcting DEA efficiency measures. Despite the multiple advantages DEA offers, the usage of this approach carries with it a number of methodological difficulties. Accounting for multiple factors of efficiency calls for more complex methods, among which the most promising are DMU clustering and calculating local production possibility frontiers. Using regression models for estimate correction requires further study due to possible systematic errors during estimation. A mixture of data correction and DMU clustering together with multi-stage DEA seems most promising at the moment. Analyzing several stages of transforming society’s resources into social welfare will allow for picking out the weak points in a state agency’s work.