Описание: Praise for the Second Edition " full of vivid and thought-provoking anecdotes... needs to be read by anyone with a serious interest in research and marketing." Research Magazine "Shmueli et al. have done a wonderful job in presenting the field
Автор: Oliviero Carugo; Frank Eisenhaber (Eds.) Название: Data Mining Techniques for the Life Sciences ISBN: 1603272402 ISBN-13(EAN): 9781603272407 Издательство: Springer Рейтинг: Цена: 17368 р. Наличие на складе: Поставка под заказ.
Описание: In this book, experts in the field contribute valuable information about the sources of information and the techniques used for "mining" new insights out of databases. The book covers a wide range of biological systems and in silico approaches.
Описание: Data warehousing and data mining provide techniques for collecting information from distributed databases and for performing data analysis. The ever expanding, tremendous amount of data collected and stored in large databases has far exceeded our human ability to comprehend--without the proper tools. There is a critical need for data analysis that can automatically analyze data, summarize it and predict future trends. In the modern age of Internet connectivity, concerns about denial of service attacks, computer viruses and worms are extremely important.Data Warehousing and Data Mining Techniques for Cyber Security contributes to the discipline of security informatics. The author discusses topics that intersect cyber security and data mining, while providing techniques for improving cyber security. Since the cost of information processing and internet accessibility is dropping, an increasing number of organizations are becoming vulnerable to cyber attacks. This volume introduces techniques for applications in the area of retail, finance, and bioinformatics, to name a few.Data Warehousing and Data Mining Techniques for Cyber Security is designed for practitioners and researchers in industry. This book is also suitable for upper-undergraduate and graduate-level students in computer science.
Автор: Tsiptsis Konstantinos Название: Data Mining Techniques in CRM ISBN: 0470743972 ISBN-13(EAN): 9780470743973 Издательство: Wiley Рейтинг: Цена: 8217 р. Наличие на складе: Поставка под заказ.
Описание: This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining.
Описание: Data warehousing is an important topic that is of interest to both the industry and the knowledge engineering research communities. Both data mining and data warehousing technologies have similar objectives and can potentially benefit from each other’s methods to facilitate knowledge discovery.Improving Knowledge Discovery through the Integration of Data Mining Techniques provides insight concerning the integration of data mining and data warehousing for enhancing the knowledge discovery process. Decision makers, academicians, researchers, advanced-level students, technology developers, and business intelligence professionals will find this book useful in furthering their research exposure to relevant topics in knowledge discovery.
Описание: Biologically-inspired data mining has a wide variety of applications in areas such as data clustering, classification, sequential pattern mining, and information extraction in healthcare and bioinformatics. Over the past decade, research materials in this area have dramatically increased, providing clear evidence of the popularity of these techniques.Biologically-Inspired Techniques for Knowledge Discovery and Data Mining exemplifies prestigious research and shares the practices that have allowed these areas to grow and flourish. This essential reference publication highlights contemporary findings in the area of biologically-inspired techniques in data mining domains and their implementation in real-life problems. Providing quality work from established researchers, this publication serves to extend existing knowledge within the research communities of data mining and knowledge discovery, as well as for academicians and students in the field.
Автор: Eric D. Kolaczyk Название: Statistical Analysis of Network Data ISBN: 144192776X ISBN-13(EAN): 9781441927767 Издательство: Springer Рейтинг: Цена: 15572 р. Наличие на складе: Поставка под заказ.
Описание: This book provides an up-to-date treatment of the foundations common to the statistical analysis of network data across the disciplines. The material is organized according to a statistical taxonomy, although the presentation balances concepts and mathematics.
Автор: Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi Название: Foundations and Novel Approaches in Data Mining ISBN: 364206650X ISBN-13(EAN): 9783642066504 Издательство: Springer Рейтинг: Цена: 26234 р. Наличие на складе: Поставка под заказ.
Описание: Data-mining has become a popular research topic in recent years for the treatment of the "data rich and information poor" syndrome. In this volume, we hope to remedy problems by (1) presenting a theoretical foundation of data-mining, and (2) providing important new directions for data-mining research.
Автор: Tsau Young Lin; Setsuo Ohsuga; Churn-Jung Liau; Xi Название: Foundations and Novel Approaches in Data Mining ISBN: 3540283153 ISBN-13(EAN): 9783540283157 Издательство: Springer Рейтинг: Цена: 26234 р. Наличие на складе: Поставка под заказ.
Описание: Presents a theoretical foundation of data-mining and provides important directions for data-mining research.
Описание: "Foundations of Data Mining and Knowledge Discovery" contains the latest results and new directions in data mining research.
Автор: Jiawei Han Название: Data Mining: Concepts and Techniques, ISBN: 0123814790 ISBN-13(EAN): 9780123814791 Издательство: Elsevier Science Рейтинг: Цена: 7508 р. Наличие на складе: Поставка под заказ.
Описание: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.
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