MARC details
| 000 -LEADER |
|---|
| fixed length control field |
08077nam a22005413i 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
EBC729031 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
MiAaPQ |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20241218094926.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
|---|
| fixed length control field |
m o d | |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
cr cnu|||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
170128s2011 xx o ||||0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9780123814807 |
| Qualifying information |
(electronic bk.) |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| Canceled/invalid ISBN |
9780123814791 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(MiAaPQ)EBC729031 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(Au-PeEL)EBL729031 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(CaPaEBR)ebr10483440 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(OCoLC)741491891 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
MiAaPQ |
| Language of cataloging |
eng |
| Description conventions |
rda |
| -- |
pn |
| Transcribing agency |
Amiu |
| Modifying agency |
MiAaPQ |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA76.9 |
| Item number |
.D34 H36 2012 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Han, Jiawei. |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Data Mining : |
| Remainder of title |
Concepts and Techniques. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
3rd ed. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Saint Louis : |
| Name of producer, publisher, distributor, manufacturer |
Elsevier Science, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2011. |
| 264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Date of production, publication, distribution, manufacture, or copyright notice |
©2012. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 online resource (740 pages) |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent. |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
computer |
| Media type code |
c |
| Source |
rdamedia. |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
online resource |
| Carrier type code |
cr |
| Source |
rdacarrier. |
| 490 1# - SERIES STATEMENT |
|---|
| Series statement |
The Morgan Kaufmann Series in Data Management Systems. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
Front Cover -- Data Mining: Concepts and Techniques -- Copyright -- Dedication -- Table of Contents -- Foreword -- Foreword to Second Edition -- Preface -- Acknowledgments -- About the Authors -- Chapter 1. Introduction -- 1.1 Why Data Mining? -- 1.2 What Is Data Mining? -- 1.3 What Kinds of Data Can Be Mined? -- 1.4 What Kinds of Patterns Can Be Mined? -- 1.5 Which Technologies Are Used? -- 1.6 Which Kinds of Applications Are Targeted? -- 1.7 Major Issues in Data Mining -- 1.8 Summary -- 1.9 Exercises -- 1.10 Bibliographic Notes -- Chapter 2. Getting to Know Your Data -- 2.1 Data Objects and Attribute Types -- 2.2 Basic Statistical Descriptions of Data -- 2.3 Data Visualization -- 2.4 Measuring Data Similarity and Dissimilarity -- 2.5 Summary -- 2.6 Exercises -- 2.7 Bibliographic Notes -- Chapter 3. Data Preprocessing -- 3.1 Data Preprocessing: An Overview -- 3.2 Data Cleaning -- 3.3 Data Integration -- 3.4 Data Reduction -- 3.5 Data Transformation and Data Discretization -- 3.6 Summary -- 3.7 Exercises -- 3.8 Bibliographic Notes -- Chapter 4. Data Warehousing and Online Analytical Processing -- 4.1 Data Warehouse: Basic Concepts -- 4.2 Data Warehouse Modeling: Data Cube and OLAP -- 4.3 Data Warehouse Design and Usage -- 4.4 Data Warehouse Implementation -- 4.5 Data Generalization by Attribute-Oriented Induction -- 4.6 Summary -- 4.7 Exercises -- 4.8 Bibliographic Notes -- Chapter 5. Data Cube Technology -- 5.1 Data Cube Computation: Preliminary Concepts -- 5.2 Data Cube Computation Methods -- 5.3 Processing Advanced Kinds of Queries by Exploring Cube Technology -- 5.4 Multidimensional Data Analysis in Cube Space -- 5.5 Summary -- 5.6 Exercises -- 5.7 Bibliographic Notes -- Chapter 6. Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods -- 6.1 Basic Concepts -- 6.2 Frequent Itemset Mining Methods. |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
6.3 Which Patterns Are Interesting?-Pattern Evaluation Methods -- 6.4 Summary -- 6.5 Exercises -- 6.6 Bibliographic Notes -- Chapter 7. Advanced Pattern Mining -- 7.1 Pattern Mining: A Road Map -- 7.2 Pattern Mining in Multilevel, Multidimensional Space -- 7.3 Constraint-Based Frequent Pattern Mining -- 7.4 Mining High-Dimensional Data and Colossal Patterns -- 7.5 Mining Compressed or Approximate Patterns -- 7.6 Pattern Exploration and Application -- 7.7 Summary -- 7.8 Exercises -- 7.9 Bibliographic Notes -- Chapter 8. Classification: Basic Concepts -- 8.1 Basic Concepts -- 8.2 Decision Tree Induction -- 8.3 Bayes Classification Methods -- 8.4 Rule-Based Classification -- 8.5 Model Evaluation and Selection -- 8.6 Techniques to Improve Classification Accuracy -- 8.7 Summary -- 8.8 Exercises -- 8.9 Bibliographic Notes -- Chapter 9. Classification: Advanced Methods -- 9.1 Bayesian Belief Networks -- 9.2 Classification by Backpropagation -- 9.3 Support Vector Machines -- 9.4 Classification Using Frequent Patterns -- 9.5 Lazy Learners (or Learning from Your Neighbors) -- 9.6 Other Classification Methods -- 9.7 Additional Topics Regarding Classification -- 9.8 Summary -- 9.9 Exercises -- 9.10 Bibliographic Notes -- Chapter 10. Cluster Analysis: Basic Concepts and Methods -- 10.1 Cluster Analysis -- 10.2 Partitioning Methods -- 10.3 Hierarchical Methods -- 10.4 Density-Based Methods -- 10.5 Grid-Based Methods -- 10.6 Evaluation of Clustering -- 10.7 Summary -- 10.8 Exercises -- 10.9 Bibliographic Notes -- Chapter 11. Advanced Cluster Analysis -- 11.1 Probabilistic Model-Based Clustering -- 11.2 Clustering High-Dimensional Data -- 11.3 Clustering Graph and Network Data -- 11.4 Clustering with Constraints -- 11.5 Summary -- 11.6 Exercises -- 11.7 Bibliographic Notes -- Chapter 12. Outlier Detection -- 12.1 Outliers and Outlier Analysis. |
| 505 8# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
12.2 Outlier Detection Methods -- 12.3 Statistical Approaches -- 12.4 Proximity-Based Approaches -- 12.5 Clustering-Based Approaches -- 12.6 Classification-Based Approaches -- 12.7 Mining Contextual and Collective Outliers -- 12.8 Outlier Detection in High-Dimensional Data -- 12.9 Summary -- 12.10 Exercises -- 12.11 Bibliographic Notes -- Chapter 13. Data Mining Trends and Research Frontiers -- 13.1 Mining Complex Data Types -- 13.2 Other Methodologies of Data Mining -- 13.3 Data Mining Applications -- 13.4 Data Mining and Society -- 13.5 Data Mining Trends -- 13.6 Summary -- 13.7 Exercises -- 13.8 Bibliographic Notes -- Bibliography -- Index. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
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. |
| 583 ## - ACTION NOTE |
|---|
| Action |
Cataloging Notes: |
| Time/date of action |
20241218 |
| Action agent |
STAMIU-0199STAMIU-0199 |
| 588 ## - SOURCE OF DESCRIPTION NOTE |
|---|
| Source of description note |
Description based on publisher supplied metadata and other sources. |
| 590 ## - LOCAL NOTE (RLIN) |
|---|
| Local note |
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Computer-assisted instruction. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining -- Handbooks, manuals, etc. |
| 655 #4 - INDEX TERM--GENRE/FORM |
|---|
| Genre/form data or focus term |
Electronic books. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Pei, Jian. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Kamber, Micheline. |
| 730 0# - ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
Academic Complete: Science and Technology. |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Relationship information |
Print version: |
| Main entry heading |
Han, Jiawei |
| Title |
Data Mining: Concepts and Techniques |
| Place, publisher, and date of publication |
Saint Louis : Elsevier Science,c2011 |
| International Standard Book Number |
9780123814791. |
| 830 #4 - SERIES ADDED ENTRY--UNIFORM TITLE |
|---|
| Uniform title |
The Morgan Kaufmann Series in Data Management Systems. |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="https://unco.idm.oclc.org/login?url=http://ebookcentral.proquest.com/lib/unco/detail.action?docID=729031">https://unco.idm.oclc.org/login?url=http://ebookcentral.proquest.com/lib/unco/detail.action?docID=729031</a> |
| Public note |
Access online |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
Book |
| Suppress in OPAC |
No |