* The research was supported by INTAS 00-397 and 00-626 Projects.Data analysis is a regular massif task of applied sciences and businesses. A huge number of algorithms were developed for different kinds of data and for particular types of data analysis. Traditional theories work with traditional databases and data structures, although the paradigm of Internet doesn’t want to wait, requiring novel technologies, able to work effectively with huge amounts of data, with data flows and uncertainties. The two current research projects, INTAS 397 and 626 are devoted to development of these issues. The paper gives the general statement, current results and examples of these researches
Data science is a multidisciplinary field that involves the use of statistical and computational tec...
This series aims to capture new developments and applications in data mining and knowledge discovery...
We discuss the KDD process in "data-flow" environments, where unstructured and time dependent data c...
* The research is supported partly by INTAS: 04-77-7173 project, http://www.intas.beThe general disc...
Data stream processing has gained increasing popularity in the last few years as an effective paradi...
Today with the advances of technology, mountainous amounts of data are now available in science, bus...
A data flow algorithm is one that gathers information about the definition and use of data in a prog...
Data mining is applied in business to find new market opportunities from data stored in operational...
Data mining is a technique for identifying patterns in large amounts of data and information. Databa...
This book presents a comprehensive and up-to-date treatise of a range of methodological and algorith...
This book explains and explores the principal techniques of Data Mining, the automatic extraction of...
Thesis (Ph. D.)--University of Rochester. Dept. of Mathematics, 2008.The algorithmic field of Data S...
Knowing what to do with the massive amount of data collected has always been an ongoing issue for ma...
The average case of some elimination-based data-flow analysis algorithms is analyzed in a mathematic...
Data Mining refers to the analysis of experimental data sets to seek out relationships and to summar...
Data science is a multidisciplinary field that involves the use of statistical and computational tec...
This series aims to capture new developments and applications in data mining and knowledge discovery...
We discuss the KDD process in "data-flow" environments, where unstructured and time dependent data c...
* The research is supported partly by INTAS: 04-77-7173 project, http://www.intas.beThe general disc...
Data stream processing has gained increasing popularity in the last few years as an effective paradi...
Today with the advances of technology, mountainous amounts of data are now available in science, bus...
A data flow algorithm is one that gathers information about the definition and use of data in a prog...
Data mining is applied in business to find new market opportunities from data stored in operational...
Data mining is a technique for identifying patterns in large amounts of data and information. Databa...
This book presents a comprehensive and up-to-date treatise of a range of methodological and algorith...
This book explains and explores the principal techniques of Data Mining, the automatic extraction of...
Thesis (Ph. D.)--University of Rochester. Dept. of Mathematics, 2008.The algorithmic field of Data S...
Knowing what to do with the massive amount of data collected has always been an ongoing issue for ma...
The average case of some elimination-based data-flow analysis algorithms is analyzed in a mathematic...
Data Mining refers to the analysis of experimental data sets to seek out relationships and to summar...
Data science is a multidisciplinary field that involves the use of statistical and computational tec...
This series aims to capture new developments and applications in data mining and knowledge discovery...
We discuss the KDD process in "data-flow" environments, where unstructured and time dependent data c...