Jiawei Han (Department of Computer ScienceUniversity of Professor, Jian Pei (Simon Fraser University, Burnaby, Canada), Hanghang Tong (Associate Professor, Department of Computer Science,
Data Mining
Concepts and Techniques
Jiawei Han (Department of Computer ScienceUniversity of Professor, Jian Pei (Simon Fraser University, Burnaby, Canada), Hanghang Tong (Associate Professor, Department of Computer Science,
Data Mining
Concepts and Techniques
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Previous edition: Burlington: Elsevier, 2012.
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Produktdetails
- Produktdetails
- The Morgan Kaufmann Series in Data Management Systems
- Verlag: Elsevier Science & Technology
- 4 ed
- Seitenzahl: 752
- Erscheinungstermin: 26. Oktober 2022
- Englisch
- Abmessung: 230mm x 190mm x 29mm
- Gewicht: 1188g
- ISBN-13: 9780128117606
- ISBN-10: 0128117605
- Artikelnr.: 64260563
- The Morgan Kaufmann Series in Data Management Systems
- Verlag: Elsevier Science & Technology
- 4 ed
- Seitenzahl: 752
- Erscheinungstermin: 26. Oktober 2022
- Englisch
- Abmessung: 230mm x 190mm x 29mm
- Gewicht: 1188g
- ISBN-13: 9780128117606
- ISBN-10: 0128117605
- Artikelnr.: 64260563
Jiawei Han is Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Well known for his research in the areas of data mining and database systems, he has received many awards for his contributions in the field, including the 2004 ACM SIGKDD Innovations Award. He has served as Editor-in-Chief of ACM Transactions on Knowledge Discovery from Data, and on editorial boards of several journals, including IEEE Transactions on Knowledge and Data Engineering and Data Mining and Knowledge Discovery.
1. Introduction
2. Data, measurements, and data processing
3. Data warehousing and online analytical processing
4. Pattern mining: basic concepts and methods
5. Pattern mining: advanced methods
6. Classification: basic concepts and methods
7. Classification: advanced methods
8. Cluster analysis: basic concepts and methods
9. Cluster analysis: advanced methods
10. Deep learning
11. Outlier Detection
12. Data mining trends and research frontiers
Appendix: Mathematical background
2. Data, measurements, and data processing
3. Data warehousing and online analytical processing
4. Pattern mining: basic concepts and methods
5. Pattern mining: advanced methods
6. Classification: basic concepts and methods
7. Classification: advanced methods
8. Cluster analysis: basic concepts and methods
9. Cluster analysis: advanced methods
10. Deep learning
11. Outlier Detection
12. Data mining trends and research frontiers
Appendix: Mathematical background
1. Introduction
2. Data, measurements, and data processing
3. Data warehousing and online analytical processing
4. Pattern mining: basic concepts and methods
5. Pattern mining: advanced methods
6. Classification: basic concepts and methods
7. Classification: advanced methods
8. Cluster analysis: basic concepts and methods
9. Cluster analysis: advanced methods
10. Deep learning
11. Outlier Detection
12. Data mining trends and research frontiers
Appendix: Mathematical background
2. Data, measurements, and data processing
3. Data warehousing and online analytical processing
4. Pattern mining: basic concepts and methods
5. Pattern mining: advanced methods
6. Classification: basic concepts and methods
7. Classification: advanced methods
8. Cluster analysis: basic concepts and methods
9. Cluster analysis: advanced methods
10. Deep learning
11. Outlier Detection
12. Data mining trends and research frontiers
Appendix: Mathematical background