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chang edward y. - foundations of large-scale multimedia information management and retrieval
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Foundations of Large-Scale Multimedia Information Management and Retrieval Mathematics of Perception




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Dettagli

Genere:Libro
Lingua: Inglese
Editore:

Springer

Pubblicazione: 08/2011
Edizione: 2011





Trama

"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.





Sommario

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).





Autore

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.










Altre Informazioni

ISBN:

9783642204289

Condizione: Nuovo
Dimensioni: 235 x 155 mm
Formato: Copertina rigida
Illustration Notes:XVIII, 291 p.
Pagine Arabe: 291
Pagine Romane: xviii


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