Data Mining - это процесс обнаружения в сырых данных ранее неизвестных, нетривиальных, практически полезных и доступных интерпретации знаний (закономерностей), необходимых для принятия решений в различных сферах человеческой деятельности. Практически все крупнейшие корпорации активно принимают участие в разработке Data Mining.
В книге приводится объективный аналитический обзор методов и программных продуктов Data Mining ...

В книге освещены основные направления в области анализа данных: организация хранилища данных, оперативный (OLAP) и интеллектуальный (Data Mining) анализ данных. Приведено описание методов и алгоритмов решения основных задач анализа: классификации,......

Книга является вторым, обновленным и дополненным, изданием учебного пособия \"Методы и модели анализа данных: OLAP и Data Mining\"....

Курс знакомит слушателей с технологией Data Mining. Подробно рассматриваются методы, задачи, применение, а также инструментальные средства и способы внедрения Data Mining в информационную инфраструктуру компании.Курс ориентирован на студентов высших учебных заведений, обучающихся по специальностям в области информационных технологий....

Книга, написанная разработчиками Microsoft SQL Server Data Mining, дает читателю полное представление о его функционировании и показывает особенности использования при решении различных задач в SQL Server 2008. Рассмотрены введение в интеллектуальный анализ данных и язык DMX....

Microsoft Data Mining approaches data mining from the particular perspective of IT professionals using Microsoft data management technologies....

This book is not just another theoretical text about statistics or data mining. No, instead it is aimed for you DBAs who want to use SQL, or bolster your understanding of statistics to support data mining and customer relationship management analytics. Each chapter is self-contained, with examples tailored to real business applications....

Data Mining in Finance presents a comprehensive overview of major algorithmic approaches to predictive data mining, including statistical, neural networks, ruled-based, decision-tree, and fuzzy-logic methods, and then examines the suitability of these approaches to financial data mining....

Data Mining and Business Intelligence: A Guide to Productivity provides an overview of data mining technology and how it is applied in a business environment. It describes the corresponding data mining methodologies that are used to solve a variety of business problems, which enhance firm-level efficiency in a less technical, more managerial style....

Data Mining: Opportunities and Challenges presents an overview of the state of the art approaches in this new and multidisciplinary field of data mining. The primary objective of this book is to explore the myriad issues regarding data mining, specifically focusing on those areas that explore new methodologies or examine case studies....

Managing Data Mining Technologies in Organizations: Techniques and Applications details the state-of-the-art data mining research, which reflects in a potpourri of chapters that demonstrate diverse use of techniques and their applications for data mining....

Most books on data mining focus on principles and furnish few instructions on how to carry out a data mining project. Data Mining Using SAS Applications not only introduces the key concepts but also enables readers to understand and successfully apply data mining methods using powerful yet user-friendly SAS macro-call files....

Reprinted from DATA MINING AND KNOWLEDGE DISCOVERY, 5:1-2 Applications of Data Mining to Electronic Commerce brings together in one place important contributions and up-to-date research results in this fast moving area....

The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines....

Marketing analysts use data mining techniques to gain a reliable understanding of customer buying habits and then use that information to develop new marketing campaigns and products. Visual mining tools introduce a world of possibilities to a much broader and non-technical audience to help them solve common business problems....

This book constitutes the refereed proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2000, held in Kyoto, Japan, in April 2000. The 33 revised full papers and 16 short papers presented were carefully reviewed and selected from a total of 116 submissions....

* First title to ever present soft computing approaches and their application in data mining, along with the traditional hard-computing approaches * Addresses the principles of multimedia data compression techniques (for image, video, text) and their role in data mining * Discusses principles and classical algorithms on string matching and their ro...

This book presents a comprehensive review of basic concepts on both data mining and evolutionary algorithms and discusses significant advances in the integration of these two areas. The authors emphasize the importance of discovering comprehensible, interesting knowledge, which is potentially useful for intelligent decision making....

Despite being a young field of research and development, data mining has proved to be a successful approach to extracting knowledge from huge collections of structured digital data collection as usually stored in databases....

This volume is the result of a two-year project aimed at coalescing the concepts and techniques of granular computing on one side, and rough set theory on another....

The ability to analyze and understand massive data sets lags far behind the ability to gather and store the data. To meet this challenge, knowledge discovery and data mining (KDD) is growing rapidly as an emerging field....

In the first part, this book analyzes the knowledge discovery process in order to understand the relations between knowledge discovery steps and focusing....

This book constitutes the refereed proceedings of the First International Workshop on Machine Learning and Data Mining in Pattern Recognition, MLDM\'99, held in Leipzig, Germany in September 1999. The 15 revised full papers presented together with two invited contributions were carefully reviewed....

This book constitutes the refereed proceedings of the 6th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2002, held in Taipei, Taiwan, in May 2002. The 32 revised full papers and 20 short papers presented together with 4 invited contributions were carefully reviewed and selected from a total of 128 submissions....

The book aims to merge Computational Intelligence with Data Mining, which are both hot topics of current research and industrial development, Computational Intelligence, incorporates techniques like data fusion, uncertain reasoning, heuristic search, learning, and soft computing....

This book teaches newcomers all they need to know to profit from today\'s powerful data mining technologies.Through extensive case studies and examples, you\'ll learn how companies are using data mining right now to achieve powerful results -- and how you can do it, too....

Data Mining for Design and Manufacturing: Methods and Applications is the first book that brings together research and applications for data mining within design and manufacturing....

With advanced computer technologies and their omnipresent usage, data accumulates in a speed unmatchable by the human\'s capacity to process data. To meet this growing challenge, the research community of knowledge discovery from databases emerged....

Recent advances in the data collection and storage technologies have made it possible for companies (e.g. bar-code technology), administrative agencies (e.g. census data) and scientific laboratories (e.g. molecule databases in chemistry or biology) to keep vast amounts of data relating to their activities....

An expert guide for applying data mining with uncertain reasoning to a wide range of uses This volume presents a holistic view of data mining by integrating this diverse and exciting field with uncertain reasoning....

Rough Sets and Data Mining: Analysis of Imprecise Data is an edited collection of research chapters on the most recent developments in rough set theory and data mining. The chapters in this work cover a range of topics that focus on discovering dependencies among data, and reasoning about vague, uncertain and imprecise information....

This book constitutes the refereed proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD-98, held in Melbourne, Australia, in April 1998. The book presents 30 revised full papers selected from a total of 110 submissions; also included are 20 poster presentations....

With the unprecedented growth-rate at which data is being collected and stored electronically today in almost all fields of human endeavor, the efficient extraction of useful information from the data available is becoming an increasing scientific challenge and a massive economic need....

Book DescriptionOften considered more as an art than a science, the field of clustering has been dominated by learning through examples and by techniques chosen almost through trial-and-error....

Book DescriptionThis book focuses on dealing with large-scale data, a field commonly referred to as data mining. The book is divided into three sections....

Book DescriptionThe goal of this book is to help readers understand state-of-the-art techniques in biological data mining and data management and includes topics such as: - preprocessing tasks such as data cleaning and data integration as applied to biological data - classification and clustering techniques for microarrays - comparison of RNA struc...

Book DescriptionManaging Data Mining: Advice from Experts is a collection of leading business applications in the data mining and multivariate modeling spectrum provided by experts in the field at leading US corporations....

Whether you are a software developer, systems architect, data analyst, or business analyst, if you want to take advantage of data mining in the development of advanced analytic applications, Java Data Mining, JDM, the new standard now implemented in core DBMS and data mining/analysis software, is a key solution component....

Data Mining, the automatic extraction of implicit and potentially useful information from data, is increasingly used in commercial, scientific and other application areas. This book explains and explores the principal techniques of Data Mining: for classification, generation of association rules and clustering....

Genome Exploitation: Data Mining the Genome is developed from the 23rd Stadler Genetic Symposium. This volume discusses and illustrates how scientists are going to characterize and make use of the massive amount of information being accumulated about the plant and animal genomes....

Data mining has emerged as a significant technology for gaining knowledge from vast quantities of data. However, concerns are growing that use of this technology can violate individual privacy. These concerns have led to a backlash against the technology, for example, a \"Data-Mining Moratorium Act\" introduced in the U.S....

\"Intelligent Data Mining – Techniques and Applications\" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications....

This book aims to present state-of-the-art analytical methods from statistics and data mining for the analysis of high-throughput data from genomics and proteomics. Research and development in genomics and proteomics depend on the analysis and interpretation of large amounts of data generated by high-throughput techniques....

The technologies in data mining have been successfully applied to bioinformatics research in the past few years, but more research in this field is necessary. While tremendous progress has been made over the years, many of the fundamental challenges in bioinformatics are still open....

The development of e-learning systems, particularly web-based education systems, has increased exponentially in recent years. In the last years, researchers have begun to investigate various data mining methods to help teachers improve e-learning systems. These methods allow them to discover new knowledge based on students\' usage data....

As with any burgeoning technology that enjoys commercial attention, the use of data mining is surrounded by a great deal of hype. Exaggerated reports tell of secrets that can be uncovered by setting algorithms loose on oceans of data. But there is no magic in machine learning, no hidden power, no alchemy....

This book constitutes the refereed proceedings of the 7th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2003, held in Seoul, Korea in April/Mai 2003. The 38 revised full papers and 20 revised short papers presented together with two invited industrial contributions were carefully reviewed and selected from 215 submissions....

With the rapid progress in high performance computers, database systems, data warehouse systems, remote sensing, telecommunication systems, data collection tools, data storage devices, and the world wide web, the amount of data being collected and made available has grown rapidly, far exceeding the capability of scientists, engineers, and business ...

Uncertainty Handling and Quality Assessment in Data Mining provides an introduction to the application of these concepts in Knowledge Discovery and Data Mining. It reviews the state-of-the-art in uncertainty handling and discusses a framework for unveiling and handling uncertainty....

The increasing volume of data in modern business and science calls for more complex and sophisticated tools....