Foundations of Large-Scale Multimedia Information Management and Retrieval Mathe

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2011
Foundations of Large-Scale Multimedia Information Management and RetrievalMathematics of PerceptionAuthors:

• Edward Y. Chang
• …show all 1hide
  

ISBN: 978-3-642-20428-9 (Print) 978-3-642-20429-6  (Online)

Mathematics of Perception

Chang, Edward Y.

Jointly published with Tsinghua University Press
2011, XVIII, 291 p. 108 illus., 60 in color.



ISBN 978-3-642-20429-6

  Immediately available per PDF-download (no DRM, watermarked)

About this book

• Written by the utmost expert at Google Inc Dr Edward Chang, Director of Research
•                                         Covering knowledge representation, semantic analysis, and scalability issues in one comprehensive book
•                                         Written for the specialist while maintaining an accessible approach for students alike
•                                         A must-have in this ever-faster evolving area
  

"Foundations of Large-Scale Multimedia Information Management and Retrieval: Mathematics of Perception"covers knowledge representation and semantic analysis of multimedia data and scalability in signal extraction, data mining, and indexing. The book is divided into two parts: Part I - Knowledge Representation and Semantic Analysis focuses on the key components of mathematics of perception as it applies to data management and retrieval. These include feature selection/reduction, knowledge representation, semantic analysis, distance function formulation for measuring similarity, and multimodal fusion. Part II - Scalability Issues presents indexing and distributed methods for scaling up these components for high-dimensional data and Web-scale datasets. The book presents some real-world applications and remarks on future research and development directions.
The book is designed for researchers, graduate students, and practitioners in the fields of Computer Vision, Machine Learning, Large-scale Data Mining, Database, and Multimedia Information Retrieval.
Dr. Edward Y. Chang was a professor at the Department of Electrical & Computer Engineering, University of California at Santa Barbara, before he joined Google as a research director in 2006. Dr. Chang received his M.S. degree in Computer Science and Ph.D degree in Electrical Engineering, both from Stanford University.

Table of contents Part I - Knowledge Representation and Semantic Analysis.- 1. Mathematics of Perception.- 2. Supervised Learning (based on tutorial DASFAA 2003).- 3. Query Concept Learning (based on IEEE TMM 2005).- 4. Feature Extraction.- 5. Feature Reduction (based on MM 04, ICME 05, IPAM).- 6. Similarity (based on MMJ 2002, CIKM 04, ICML 05).- Part II - Scalability Issues.- 7. Imbalanced Data Learning (based on TKDE 2005).- 8. Semantics Fusion (based on MM 04, MM05, KDD 08).- 9. Kernel Machines Speedup (based on SDM 05, KDD 06, NIPS 07).- 10. Kernel Indexing (based on TKDE 06).- 11. Put It All Together (based on SPIE 06).

Distribution rights Distribution rights in China: Tsinghua University Press.

• Authors & Editors
  

Dr. Edward Y. Chang was a professor at the Department of Electrical & Computer Engineering, University of California at Santa Barbara, before he joined Google as a research director in 2006. Dr. Edward Y. Chang received his M.S. degree in Computer Science and Ph.D degree in Electrical Engineering, both from Stanford University.


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关键词：information Foundations Large-Scale foundation Informatio Foundations Large-Scale Multimedia Information Management

在谷歌公司，研究主任爱德华昌博士写的最大的专家
                                        覆盖于一体的综合性本书的知识表示，语义分析，和可伸缩性问题
                                        撰稿专家，同时保持一个可访问的方式为学生的一致好评
                                        必须具备在这个不断更快发展区
“大型多媒体信息管理和检索的基础：数学知觉”涵盖多媒体信号提取，数据挖掘和索引数据和可扩展性的知识表示和语义分析。本书分为两个部分：第一部分 - 知识表示方法和语义分析侧重于感知数学的关键组成部分，因为它适用于数据管理和检索。这些措施包括功能选择/减少，知识表示，语义分析，制定测量相似距离函数，以及多模态融合。第二部分 - 可扩展性问题索引和分布式方法为扩大这些元件的高维数据和网络规模的数据集。这本书提出了一些现实世界的应用和未来的研究和发展方向的言论。
本书是专为在计算机视觉，机器学习，大规模数据挖掘，数据库，多媒体信息检索等领域的研究人员，研究生和从业人员。
渝昌博士是一个系，加州大学圣巴巴拉分校电子与计算机工程系教授，之前，他作为研究总监，2006年加入谷歌。张博士获得了他的M.S.计算机科学与电气工程博士学位，从斯坦福大学的学位。