รายละเอียดในรูปแบบ MARC
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05284nam a2200289 a 4500 |
| 001 - CONTROL NUMBER |
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29808 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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20230423231329.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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130910s2012 us m a001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780123814791 |
| 049 ## - LOCAL HOLDINGS (OCLC) |
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| -- |
PITLIB |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
QA76.9.D343 |
| Item number |
H233 2012 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Han, Jiawei |
| 9 (RLIN) |
38924 |
| 245 10 - TITLE STATEMENT |
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| Title |
Data mining : |
| Remainder of title |
concepts and techniques / |
| Statement of responsibility, etc. |
Jiawei Han, Micheline Kamber, Jian Pei |
| Medium |
[book] |
| 250 ## - EDITION STATEMENT |
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| Edition statement |
3rd ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
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| Place of publication, distribution, etc. |
Burlington, MA : |
| Name of publisher, distributor, etc. |
Elsevier, |
| Date of publication, distribution, etc. |
c2012. |
| -- |
19772 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xxxii, 703 p. : |
| Other physical details |
ill. |
| 449 #0 - |
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| -- |
•v004– New Arrivals- Sep. 2013 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
includes index |
| 505 #0 - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Chapter 1. Introduction -- |
| Title |
Index. |
| -- |
1.2 What Is Data Mining? -- |
| -- |
1.-- |
| -- |
3 What Kinds of Data Can Be Mined? -- |
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1.4 What Kinds of Patterns Can Be Mined? -- |
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1.5 Which Technologies Are Used? -- |
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1.6 Which Kinds of Applications Are Targeted? -- |
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1.7 Major Issues in Data Mining-- |
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1.8 Summary-- |
| -- |
1.9 Exercises-- |
| -- |
1.10 Bibliographic Notes-- |
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Chapter 2. Getting to Know Your Data-- |
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2.1 Data Objects and Attribute Types-- |
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2.2 Basic Statistical Descriptions of Data-- |
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2.-- |
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3 Data Visualization-- |
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2.4 Measuring Data Similarity and Dissimilarity-- |
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2.5 Summary-- |
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2.6 Exercises-- |
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2.7 Bibliographic Notes-- |
| -- |
Chapter -- |
| -- |
3. Data Preprocessing-- |
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-- |
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3.1 Data Preprocessing: An Overview-- |
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3.2 Data Cleaning-- |
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3.3 Data Integration-- |
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3.4 Data Reduction-- |
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3.5 Data Transformation and Data iscretization-- |
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3.6 Summary-- |
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3.7 Exercises-- |
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3.8 Bibliographic Notes-- |
| -- |
Chapter -- |
| -- |
4. Data Warehousing and Online Analytical Processing-- |
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4.1 Data Warehouse: Basic Concepts-- |
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4.2 Data Warehouse Modeling: Data Cube and OLAP-- |
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4. 3 Data Warehouse Design and Usage-- |
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4.4 Data Warehouse Implementation-- |
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4.5 Data Generalization by Attribute-Oriented Induction-- |
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4.6 Summary-- |
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4.7 Exercises-- |
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4.8 Bibliographic Notes-- |
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Chapter 5. Data Cube Technology-- |
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5.1 Data Cube Computation: Preliminary Concepts-- |
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5.2 Data Cube Computation Methods-- |
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5. 3 Processing Advanced Kinds of Queries by Exploring Cube Technology-- |
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5.4 Multidimensional Data Analysis in Cube Space-- |
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5.5 Summary-- |
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5.6 Exercises-- |
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5.7 Bibliographic Notes-- |
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Chapter 6. Mining Frequent Patterns, Associations, and Correlations: Basic Concepts and Methods-- |
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6.1 Basic Concepts-- |
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6.2 Frequent Itemset Mining Methods-- |
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6. 3 Which Patterns Are Interesting?--Pattern Evaluation Methods-- |
| -- |
6.4 Summary-- |
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6.5 Exercises-- |
| -- |
6.6 Bibliographic Notes-- |
| -- |
Chapter t 7. Advanced Pattern Mining-- |
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7.1 Pattern Mining: A Road Map-- |
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7.2 Pattern Mining in Multilevel, Multidimensional Space-- |
| -- |
7. 3 Constraint-Based Frequent Pattern Mining-- |
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7.4 Mining High-Dimensional Data and Colossal Patterns-- |
| -- |
7.5 Mining Compressed or Approximate Patterns-- |
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7.6 Pattern Exploration and Application-- |
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7.7 Summary-- |
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7.8 Exercises-- |
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7.9 Bibliographic Notes-- |
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Chapter 8. Classification: Basic Concepts-- |
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8.1 Basic Concepts-- |
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8.2 Decision Tree Induction-- |
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8.3 Bayes Classification Methods-- |
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8.4 Rule-Based Classification-- |
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8.5 Model Evaluation and Selection-- |
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8.6 Techniques to Improve Classification Accuracy-- |
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8.7 Summary-- |
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8.8 Exercises-- |
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8.9 Bibliographic Notes-- |
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Chapter 9. Classification: Advanced Methods-- |
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9.1 Bayesian Belief Networks-- |
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9.2 Classification by Backpropagation-- |
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9.3 Support Vector Machines-- |
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9.4 Classification Using Frequent Patterns-- |
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9.5 Lazy Learners (or Learning from Your Neighbors) -- |
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9.6 Other Classification Methods-- |
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9.7 Additional Topics Regarding Classification-- |
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9.8 Summary-- |
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9.9 Exercises-- |
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9.10 Bibliographic Notes-- |
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Chapter 10. Cluster Analysis: Basic Concepts and Methods-- |
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10.1 Cluster Analysis-- |
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10.2 Partitioning Methods-- |
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10.t3 Hierarchical Methods-- |
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10.4 Density-Based Methods-- |
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10.5 Grid-Based Methods-- |
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10.6 Evaluation of Clustering-- |
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10.7 Summary-- |
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10.8 Exercises-- |
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10.9 Bibliographic Notes-- |
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Chapter 11. Advanced Cluster Analysis-- |
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11.1 Probabilistic Model-Based Clustering-- |
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11.2 Clustering High-Dimensional Data-- |
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11.-- |
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3 Clustering Graph and Network Data-- |
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11.4 Clustering with Constraints-- |
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11.5 Summary-- |
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11.6 Exercises-- |
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11.7 Bibliographic Notes-- |
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Chapter 12. Outlier Detection-- |
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12.1 Outliers and Outlier Analysis-- |
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12.2 Outlier Detection Methods-- |
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12. 3 Statistical Approaches-- |
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12.4 Proximity-Based Approaches-- |
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12.5 Clustering-Based Approaches-- |
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12.6 Classification-Based Approaches-- |
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12.7 Mining Contextual and Collective Outliers-- |
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12.8 Outlier Detection in High-Dimensional Data-- |
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12.9 Summary-- |
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12.10 Exercises12.11 Bibliographic Notes-- |
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Chapter 13. Data Mining Trends and Research Frontiers-- |
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13.1 Mining Complex Data Types-- |
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13.2 Other Methodologies of Data Mining-- |
| -- |
1-- |
| -- |
3.3 Data Mining Applications-- |
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13.4 Data Mining and Society-- |
| -- |
13.5 Data Mining Trends-- |
| -- |
13.6 Summary-- |
| -- |
13.7 Exercises-- |
| -- |
13.8 Bibliographic Notes-- |
| -- |
Bibliography-- |
| -- |
Index. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Data mining |
| 9 (RLIN) |
17634 |
| 690 #0 - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
|---|
| Topical term or geographic name as entry element |
0023 วิศวกรรมศาสตรบัณฑิต สาขาวิศวกรรมคอมพิวเตอร์ CPE (ป.ตรี) |
| 9 (RLIN) |
65 |
| 690 #0 - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
|---|
| Topical term or geographic name as entry element |
0021 วิทยาศาสตร์บัณฑิต สาขาเทคโนโลยีสารสนเทศ IT (ป.ตรี) |
| 9 (RLIN) |
64 |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Kamber, Micheline |
| 9 (RLIN) |
38925 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Koha item type |
หนังสือ |
| 988 ## - |
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29808 |
