Data Mining: Concepts and Techniques

Front Cover
Morgan Kaufmann, 2001 - Computers - 550 pages
16 Reviews
Here's the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges. Data Mining: Concepts and Techniques equips you with a sound understanding of data mining principles and teaches you proven methods for knowledge discovery in large corporate databases.

Written expressly for database practitioners and professionals, this book begins with a conceptual introduction designed to get you up to speed. This is followed by a comprehensive and state-of-the-art coverage of data mining concepts and techniques. Each chapter functions as a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. Wherever possible, the authors raise and answer questions of utility, feasibility, optimization, and scalability, keeping your eye on the issues that will affect your project's results and your overall success.

Data Mining: Concepts and Techniques is the master reference that practitioners and researchers have long been seeking. It is also the obvious choice for academic and professional classrooms.

Classroom Features Available Online:
- instructor's manual
- course slides (in PowerPoint)
- course supplementary readings
- sample assignments and course projects

* Offers a comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data.
* Organized as a series of stand-alone chapters so you can begin anywhere and immediately apply what you learn.
* Presents dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects.
* Provides in-depth, practical coverage of essential data mining topics, including OLAP and data warehousing, data preprocessing, concept description, association rules, classification and prediction, and cluster analysis.
* 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.
  

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Review: Data Mining: Concepts and Techniques

User Review  - Somar Boubou - Goodreads

First of all, I would like to mention that I am not familiar with data mining and its technology So you can take my review as a summary of the book with my personal opinion -not a professional one ... Read full review

Review: Data Mining: Concepts and Techniques

User Review  - Daniel Korzekwa - Goodreads

I selected this book, hoping to understand the difference between Data Mining, which I wasn't familiar with yet, and the fields already known to me of Machine Learning and Statistics. This book ... Read full review

All 9 reviews »

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Copyright

Common terms and phrases

Popular passages

Page 512 - S. Guha. R. Rastogi, and K. Shim. CURE: An efficient clustering algorithm for large databases.
Page 502 - Lin, HS Sawhney, and K. Shim. Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases.
Page 526 - G. Sheikholeslami, S. Chatterjee, and A. Zhang. Wavecluster: A multi-resolution clustering approach for very large spatial databases.

References to this book

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References from web pages

Data Mining: Concepts and Techniques
Data Mining:. Concepts and Techniques. Second Edition. Jiawei Han. and. Micheline Kamber. University of Illinois at Urbana-Champaign. amsterdamboston ...
www-sal.cs.uiuc.edu/ ~hanj/ bk2/ toc.pdf

Data Mining: Concepts and Techniques — Slides for Textbook ...
Data Mining: Concepts and Techniques. 2. Appendix B. An Introduction to dbminer. System Architecture; Input and Output; Data Mining Tasks Supported by the ...
www.cs.sfu.ca/ ~han/ bk/ a2dbminer.ppt

CSE 544 Data Mining Concepts and Techniques
Textbook:. Jiawei Han, Micheline Kamber, DATA MINING Concepts and Techniques, Morgan Kaufman Publishers, 2001. Course Description: ...
www.cs.sunysb.edu/ ~cse544/

Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques. 3. Why Data Mining Primitives and. Languages? Finding all the patterns autonomously in a database? ...
www.ir.iit.edu/ ~dagr/ DataMiningCourse/ Spring2001/ BookNotes/ 4lang.pdf

Data Mining: Concepts and Techniques — Slides for Textbook ...
Data Mining: Concepts and Techniques. 2. Cluster Analysis. What is Cluster Analysis? Types of Data in Cluster Analysis; A Categorization of Major Clustering ...
www.informatics.indiana.edu/ predrag/ classes/ 2005springi400/ Lecture_15_2.ppt

Data Mining: Concepts and Techniques — Chapter 4 —
Data Mining: Concepts and Techniques. 2. Chapter 4: Data Cube Computation and Data Generalization. Efficient Computation of Data Cubes; Exploration and ...
210.70.108.81/ Univesity_Day_Fourth_Grade/ DataWarehousing& Mining/ DataCubeComp.ppt

citeulike: Data Mining: Concepts and Techniques (The Morgan ...
Data Mining: Concepts and Techniques equips you with a sound understanding of data mining principles and teaches you proven methods for knowledge discovery ...
www.citeulike.org/ user/ jychen/ article/ 267589

Data Mining: Concepts and Techniques — Chapter 1 ...
Data Mining: Concepts and Techniques. Morgan Kaufmann, 2nd ed., 2006; dj Hand, H. Mannila, and P. Smyth, Principles of Data Mining, MIT Press, 2001 ...
delab.csd.auth.gr/ ~manolopo/ oikonomiko/ edition2slides/ 01.ppt

Course Offer for 2000-2001 Spring Semester
Data Mining Concepts and Techniques, 2ed by Jiawei Han, Kamber M Morgan Kaufmann Publishers 2005; Data Mining : Practical Machine Learning Tools and ...
www.mis.boun.edu.tr/ badur/ mis542/ MIS%20542%20Syllabus%2008.doc

Data Mining: Concepts and Techniques — Slides for Textbook ...
(required) J. Han, M. Kamber, Data Mining: Concepts and Techniques, 2001. Additional papers and handouts relevant to presented topics will be distributed as ...
www.ist.temple.edu/ ~vucetic/ cis526fall2004/ lecture1.ppt

About the author (2001)

Simon Fraser University, British Columbia, Canada

Simon Fraser University, British Columbia, Canada