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Concepts and Methods for Data Mining offer the framework for understanding and using the methods for analyzing data or information for usage in a range of contexts. Data mining is defined, along with the methods and software used to extract insights from large datasets. The term "knowledge discovery from data" (KDD) is used to describe the content of this book. It examines the practicality, utility, efficiency, and scalability of methods for handling massive data volumes. This new version begins with a description of data mining and then moves on to techniques for discovering, preprocessing, processing, and storing data. Following that, the data warehouses, OLAP, as well as data cube technologies are discussed. Then, the procedures for discovering repeating structures in huge datasets are outlined. This book explains all you need to know about data clustering and classification techniques. The subsequent chapters explore data mining's patterns, uses, and potential future directions, with a focus on outlier identification. The book is meant for readers interested in data mining, including CS students, software developers, company executives, and academics.
The book starts with an introduction that covers the fundamentals, including Database User's Database Languages, & Administrators, Database Design, as well as Data Storage, and Querying. The conceptual design, the logical design, and the physical design are the three stages that are covered in this book, which follow the conventional approach for the construction of databases. Understanding the process of researching databases and constructing databases may be made easier with the help of this technique, which is logical and organized. The content that is provided in this book has a strong focus on applications, practical problems, and implementation, in addition to providing a full discussi...
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Vol. 1 contains papers from the 8th Conference on Asian Affairs held in 1959 at the University of Illinois.