Challenges at the Interface of Data Analysis, Computer Science, and Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Challenges at the Interface of Data Analysis, Computer Science, and Optimization write by Wolfgang A. Gaul. This book was released on 2012-02-06. Challenges at the Interface of Data Analysis, Computer Science, and Optimization available in PDF, EPUB and Kindle. This volume provides approaches and solutions to challenges occurring at the interface of research fields such as data analysis, computer science, operations research, and statistics. It includes theoretically oriented contributions as well as papers from various application areas, where knowledge from different research directions is needed to find the best possible interpretation of data for the underlying problem situations. Beside traditional classification research, the book focuses on current interests in fields such as the analysis of social relationships as well as statistical musicology.
Frontiers in Massive Data Analysis
Frontiers in Massive Data Analysis - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Frontiers in Massive Data Analysis write by National Research Council. This book was released on 2013-09-03. Frontiers in Massive Data Analysis available in PDF, EPUB and Kindle. Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
Modern Quantification Theory
Modern Quantification Theory - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Modern Quantification Theory write by Shizuhiko Nishisato. This book was released on 2021-07-22. Modern Quantification Theory available in PDF, EPUB and Kindle. This book offers a new look at well-established quantification theory for categorical data, referred to by such names as correspondence analysis, dual scaling, optimal scaling, and homogeneity analysis. These multiple identities are a consequence of its large number of properties that allow one to analyze and visualize the strength of variable association in an optimal solution. The book contains modern quantification theory for analyzing the association between two and more categorical variables in a variety of applicative frameworks. Visualization has attracted much attention over the past decades and given rise to controversial opinions. One may consider variations of plotting systems used in the construction of the classic correspondence plot, the biplot, the Carroll-Green-Schaffer scaling, or a new approach in doubled multidimensional space as presented in the book. There are even arguments for no visualization at all. The purpose of this book therefore is to shed new light on time-honored graphical procedures with critical reviews, new ideas, and future directions as alternatives. This stimulating volume is written with fresh new ideas from the traditional framework and the contemporary points of view. It thus offers readers a deep understanding of the ever-evolving nature of quantification theory and its practice. Part I starts with illustrating contingency table analysis with traditional joint graphical displays (symmetric, non-symmetric) and the CGS scaling and then explores logically correct graphs in doubled Euclidean space for both row and column variables. Part II covers a variety of mathematical approaches to the biplot strategy in graphing a data structure, providing a useful source for this modern approach to graphical display. Part II is also concerned with a number of alternative approaches to the joint graphical display such as bimodal cluster analysis and other statistical problems relevant to quantification theory.
Data Science, Learning by Latent Structures, and Knowledge Discovery
Data Science, Learning by Latent Structures, and Knowledge Discovery - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Data Science, Learning by Latent Structures, and Knowledge Discovery write by Berthold Lausen. This book was released on 2015-05-06. Data Science, Learning by Latent Structures, and Knowledge Discovery available in PDF, EPUB and Kindle. This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data; advances in classification, clustering and pattern recognition methods; strategies for modeling complex data and mining large data sets; applications of advanced methods in specific domains of practice. The contributions offer interesting applications to various disciplines such as psychology, biology, medical and health sciences; economics, marketing, banking and finance; engineering; geography and geology; archeology, sociology, educational sciences, linguistics and musicology; library science. The book contains the selected and peer-reviewed papers presented during the European Conference on Data Analysis (ECDA 2013) which was jointly held by the German Classification Society (GfKl) and the French-speaking Classification Society (SFC) in July 2013 at the University of Luxembourg.
Challenges at the Interface of Data Analysis, Computer Science, and Optimization
Challenges at the Interface of Data Analysis, Computer Science, and Optimization - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Challenges at the Interface of Data Analysis, Computer Science, and Optimization write by Wolfgang Gaul. This book was released on 2012-02-13. Challenges at the Interface of Data Analysis, Computer Science, and Optimization available in PDF, EPUB and Kindle. This volume provides approaches and solutions to challenges occurring at the interface of research fields such as data analysis, computer science, operations research, and statistics. It includes theoretically oriented contributions as well as papers from various application areas, where knowledge from different research directions is needed to find the best possible interpretation of data for the underlying problem situations. Beside traditional classification research, the book focuses on current interests in fields such as the analysis of social relationships as well as statistical musicology.
