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Author:   Xiaochun Wang, Ph.D. (Xi’an Tuowei-High-Tech Corporation, Xi'an, China)
Publisher:   Elsevier Science & Technology
Imprint:   Morgan Kaufmann Publishers In
Weight:   0.450kg
ISBN:  

9780443405419

ISBN 10:   0443405417
Pages:   364
Publication Date:   07 May 2026
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
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Table of Contents

Part I: Foundation 1. Overview and Contributions 2. Introduction to Data Mining Algorithms 3. Introduction to Data Compression Methods Part II: Association Rule Mining 4. Huffman Coding for Association Rule Mining 5. Arithmetic Coding for Maximal Frequent Itemsets Mining Part III: Classification 6. Feature Subset Selection for Decision Tree Construction 7. Neural Networks for Decision Tree Construction 8. Principal Component Analysis for Decision Tree Construction 9. Dictionary Techniques for Support Vector Machine 10. Quantization for Support Vector Machine Part IV: Clustering and Outlier Detection 11. A Sparse Data Representation for Clustering 12. Dictionary Coding Based Compression for Clustering 13. Nearest Neighbor Based Compression for Outlier Detection 14. Huffman Coding for Outlier Detection 15. Arithmetic Coding for Outlier Detection

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Author Information

Dr. Xiaochun Wang received her BS degree from Beijing University and her MS degree in data compression and PhD degree in mobile robotics from the Department of Electrical Engineering and Computer Science at Vanderbilt University. She was an associate professor at the School of Software Engineering at Xi’an Jiaotong University and taught Database Management and Data Mining courses from 2010 to 2021. She currently works as a senior scientist at Xi’an Tuowei Hi-Tech Corporation. Her research interests include data mining, pattern recognition, signal processing, and computer vision.

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