Data Mining Concepts and Techniques

This book explores the concepts and techniques of knowledge discovery and data mining. As amultidisciplinaryfield, datamining draws on work from areas including statistics, machine learning, pattern recognition, database technology, information retrieval, network science, knowledge-based systems, artificial intelligence, high-performance computing, and data visualization.

Data Mining Concepts and Techniques

Jiawei Han, Micheline Kamber, Jian Pei

Morgan Kaufmann Publishers

2011

Abstract

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.

Citation

Han, Jiawei, Micheline Kamber, and Jian Pei. "Data mining concepts and techniques third edition." The Morgan Kaufmann Series in Data Management Systems 5.4 (2011): 83-124.

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