Data Mining: Concepts and Techniques / Edition 3 by Jiawei Han, Micheline Kamber, Jian Pei | | 9780123814791 | Hardcover | Barnes & Noble
Data Mining: Concepts and Techniques / Edition 3

Data Mining: Concepts and Techniques / Edition 3

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by Jiawei Han, Micheline Kamber, Jian Pei
     
 

ISBN-10: 0123814790

ISBN-13: 9780123814791

Pub. Date: 07/06/2011

Publisher: Elsevier Science

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,

Overview

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.

    * Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects.
    • Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields. *Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

    Product Details

    ISBN-13:
    9780123814791
    Publisher:
    Elsevier Science
    Publication date:
    07/06/2011
    Series:
    Morgan Kaufmann Series in Data Management Systems Series
    Pages:
    744
    Sales rank:
    387,717
    Product dimensions:
    7.80(w) x 9.30(h) x 1.70(d)

    Table of Contents

    Chapter 1Introduction

    Chapter 2. Getting to Know Your Data

    Chapter 3. Preprocessing: Data Reduction, Transformation, and Integration

    Chapter 4. Data Warehousing and On-Line Analytical Processing

    Chapter 5. Data Cube Technology

    Chapter 6. Mining Frequent Patterns, Associations and Correlations: Concepts and

    Methods

    Chapter 7. Advanced Frequent Pattern Mining

    Chapter 8. Classification: Basic Concepts

    Chapter 9. Classification: Advanced Methods

    Chapter 10. Cluster Analysis: Basic Concepts and Methods

    Chapter 11. Cluster Analysis: Advanced Methods

    Chapter 12. Outlier Analysis

    Chapter 13. Trends and Research Frontiers in Data Mining

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