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Data Mining: Concepts & Techniques - 2nd Edition : Han & Kamber (HC, 2006)

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Item specifics

Condition
Acceptable: A book with obvious wear. May have some damage to the cover but integrity still intact. ...
Country/Region of Manufacture
United States
Narrative Type
Nonfiction
Original Language
English
ISBN
9781558609013
Subject Area
Computers
Publication Name
Data Mining, Southeast Asia Edition
Publisher
Elsevier Science & Technology
Item Length
9.3 in
Subject
Intelligence (Ai) & Semantics, Databases / Data Mining, Databases / General
Publication Year
2006
Series
The Morgan Kaufmann Series in Data Management Systems Ser.
Type
Textbook
Format
Hardcover
Language
English
Item Height
0.6 in
Author
Jian Pei, Jiawei Han, Micheline Kamber
Features
Revised
Item Weight
60.1 Oz
Item Width
7.5 in
Number of Pages
800 Pages

About this product

Product Information

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. A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data Updates that incorporate input from readers, changes in the field, and more material on statistics and machine learning Dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects Complete classroom support for instructors at www.mkp.com/datamining2e companion site

Product Identifiers

Publisher
Elsevier Science & Technology
ISBN-10
1558609016
ISBN-13
9781558609013
eBay Product ID (ePID)
45420712

Product Key Features

Number of Pages
800 Pages
Language
English
Publication Name
Data Mining, Southeast Asia Edition
Publication Year
2006
Subject
Intelligence (Ai) & Semantics, Databases / Data Mining, Databases / General
Features
Revised
Type
Textbook
Subject Area
Computers
Author
Jian Pei, Jiawei Han, Micheline Kamber
Series
The Morgan Kaufmann Series in Data Management Systems Ser.
Format
Hardcover

Dimensions

Item Height
0.6 in
Item Weight
60.1 Oz
Item Length
9.3 in
Item Width
7.5 in

Additional Product Features

Edition Number
2
LCCN
2006-296324
Reviews
"Now, for the first time, there is an outstanding text on data mining which covers the science as well as the process in a comprehensive manner and with great lucidity." --Laks Lakshmanan, Concordia University, on the 1st ed: The second edition of Han and Kamber Data Mining: Concepts and Techniques updates and improves the already comprehensive coverage of the first edition and adds coverage of new and important topics, such as mining stream data, mining social networks, and mining spatial, multi-media and other complex data. This book will be an excellent textbook for courses on Data Mining and Knowledge Discovery.Gregory Piatetsky-Shapiro, President, KDnuggets The second edition is the most complete and up-to-date presentation on this topic. Compared to the already comprehensive and thorough coverage of the first edition it adds the state-of-the-art research results in new topics such as mining stream, time-series and sequence data as well as mining spatial, multimedia, text and web data. This book is a "must have" for all instructors, researchers, developers and users in the area of data mining and knowledge discovery. ?Hans-Peter Kriegel, University of Munich, Germany, "Now, for the first time, there is an outstanding text on data mining which covers the science as well as the process in a comprehensive manner and with great lucidity." --Laks Lakshmanan, Concordia University, on the 1st ed:, "Now, for the first time, there is an outstanding text on data mining which covers the science as well as the process in a comprehensive manner and with great lucidity." --Laks Lakshmanan, Concordia University, on the 1st ed: The second edition of Han and Kamber Data Mining: Concepts and Techniques updates and improves the already comprehensive coverage of the first edition and adds coverage of new and important topics, such as mining stream data, mining social networks, and mining spatial, multi-media and other complex data. This book will be an excellent textbook for courses on Data Mining and Knowledge Discovery. Gregory Piatetsky-Shapiro , President, KDnuggets The second edition is the most complete and up-to-date presentation on this topic. Compared to the already comprehensive and thorough coverage of the first edition it adds the state-of-the-art research results in new topics such as mining stream, time-series and sequence data as well as mining spatial, multimedia, text and web data. This book is a "must have" for all instructors, researchers, developers and users in the area of data mining and knowledge discovery. - Hans-Peter Kriegel , University of Munich, Germany, "Jiawei, Micheline, and Jian give an encyclopedic coverage of all the related methods, from the classic topics of clustering and classification, to database methods (association rules, data cubes) to more recent and advanced topics (SVD/PCA , wavelets, support vector machines).. Overall, it is an excellent book on classic and modern data mining methods alike, and it is ideal not only for teaching, but as a reference book."- Christos Faloutsos, Carnegie Mellon University, The second edition of Han and Kamber Data Mining: Concepts and Techniques updates and improves the already comprehensive coverage of the first edition and adds coverage of new and important topics, such as mining stream data, mining social networks, and mining spatial, multi-media and other complex data. This book will be an excellent textbook for courses on Data Mining and Knowledge Discovery. Gregory Piatetsky-Shapiro, President, KDnuggets The second edition is the most complete and up-to-date presentation on this topic. Compared to the already comprehensive and thorough coverage of the first edition it adds the state-of-the-art research results in new topics such as mining stream, time-series and sequence data as well as mining spatial, multimedia, text and web data. This book is a "must have" for all instructors, researchers, developers and users in the area of data mining and knowledge discovery. Hans-Peter Kriegel, University of Munich, Germany
Target Audience
College Audience
Illustrated
Yes
Edition Description
Revised Edition
Lc Classification Number
Qa76.9 D343 H36 2006
Table of Content
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
Copyright Date
2006

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Most relevant reviews

  • Data Mining

    Bought this book as an addon to my thesis' research on Data Mining. Most specifically I was looking for in depth knowledge on Market Basket analysis which this book has successfully satisfied my requirements in a few pages. Also, it has very good coverage on OLAP and cubing features (not mentioning other various data mining techniques!!). Personally I recommend this book as its English is easy to follow and understand without getting into too much technicalities and jargon. However, there are might be areas that either you have to have some prior knowledge or at least make some extra research; such as statistics. In future editions, I would love to see actual code implementations rather than algorithms but overall, I found it useful for what I've bought it for.