Foundations of Large-Scale Multimedia Information Management and Retrieval

Mathematics of Perception
2011
ISBN: 978-3-642-20428-9
Verlag: Springer

Buch, Englisch, 291 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 635 g

"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, MachineLearning, 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.

Zielgruppe

Research

Autoren/Hrsg.

Chang, Edward Y.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Professionelle Anwendung Multimedia
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Information Retrieval

Inhaltsverzeichnis

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).

Über Autor(innen)

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.