Data mining : concepts and techniques

Bibliographic Information

Data mining : concepts and techniques

Jiawei Han, Micheline Kamber

(The Morgan Kaufmann series in data management systems)

Morgan Kaufmann Pub., an imprint of Elsevier, c2006

2nd ed

Available at  / 44 libraries

Search this Book/Journal

Note

Includes bibliographical references (p. 703-743) and index

Description and Table of Contents

Description

Our ability to generate and collect data has been increasing rapidly. Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge. Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data- including stream data, sequence data, graph structured data, social network data, and multi-relational data.

Table of Contents

1. Introduction 2. Data Preprocessing 3. Data Warehouse and OLAP Technology: An Overview 4. Data Cube Computation and Data Generalization 5. Mining Frequent Patterns, Associations, and Correlations 6. Classification and Prediction 7. Cluster Analysis 8. Mining Stream, Time-Series, and Sequence Data 9 Graph Mining, Social Network Analysis, and Multi-Relational Data Mining 10. Mining Object, Spatial, Multimedia, Text, and Web Data 11. Applications and Trends in Data Mining Appendix A: An Introduction to Microsoft's OLE DB for Data Mining

by "Nielsen BookData"

Related Books: 1-1 of 1

Details

  • NCID
    BA75936048
  • ISBN
    • 9781558609013
  • Country Code
    ne
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Amsterdam ; San Francisco, CA ; Tokyo
  • Pages/Volumes
    xxviii, 770 p.
  • Size
    25 cm
  • Classification
  • Subject Headings
  • Parent Bibliography ID
Page Top