Multimedia data require specialised management techniques because the representations of colour, time, semantic concepts, and other underlying information can be drastically different from one another. This textbook on multimedia data management techniques gives a unified perspective on retrieval efficiency and effectiveness. It provides a comprehensive treatment, from basic to advanced concepts, that will be useful to readers of different levels, from advanced undergraduate and graduate students to researchers and to professionals. After introducing models for multimedia data (images, video, audio, text, and web) and for their features, such as colour, texture, shape, and time, the book presents data structures and algorithms that help store, index, cluster, classify, and access common data representations. The authors also introduce techniques, such as relevance feedback and collaborative filtering, for bridging the 'semantic gap' and present the applications of these to emerging topics, including web and social networking.
Multimedia data require specialised management techniques because the representations of colour, time, semantic concepts, and other underlying information can be drastically different from one another. This textbook on multimedia data management techniques gives a unified perspective on retrieval efficiency and effectiveness. It provides a comprehensive treatment, from basic to advanced concepts, that will be useful to readers of different levels, from advanced undergraduate and graduate students to researchers and to professionals. After introducing models for multimedia data (images, video, audio, text, and web) and for their features, such as colour, texture, shape, and time, the book presents data structures and algorithms that help store, index, cluster, classify, and access common data representations. The authors also introduce techniques, such as relevance feedback and collaborative filtering, for bridging the 'semantic gap' and present the applications of these to emerging topics, including web and social networking.
1. Introduction: multimedia applications and data management requirements; 2. Models for multimedia data; 3. Common representations of multimedia features; 4. Feature quality and independence: why and how?; 5. Indexing, search, and retrieval of sequences; 6. Indexing, search, retrieval of graphs and trees; 7. Indexing, search, and retrieval of vectors; 8. Clustering techniques; 9. Classification; 10. Ranked retrieval; 11. Evaluation of retrieval; 12. User relevance feedback and collaborative filtering.
A wide-ranging textbook covering data structures and algorithms for storing, indexing, clustering, classifying, and accessing common multimedia data representations.
K. Selçuk Candan is a Professor of Computer Science and Engineering at Arizona State University. He received his Ph.D. in 1997 from the University of Maryland at College Park. Candan has authored more than 120 conference and journal articles, 9 patents, and many book chapters and, among his other scientific positions, has served as program chair for ACM Multimedia Conference '08, the Int. Conference on Image and Video Retrieval (CIVR'10), and as an organizing committee member for ACM SIG Management of Data Conference (SIGMOD'06). Since 2005, he has also served as an editorial board member for the Very Large Databases (VLDB) journal. Maria Luisa Sapino is a Professor in the Department of Computer Science at the University of Torino, where she also earned her Ph.D. There she leads the multimedia and heterogeneous data management group. Her scientific contributions include more than 60 conference and journal papers; her services as chair, organizer, and program committee member in major conferences and workshops on multimedia; and her collaborations with industrial research labs, including the RAI-Crit (Center for Research and Technological Innovation) and Telecom Italia Lab, on multimedia technologies.
"This text book is a complete and excellent treatment of multimedia
information retrieval and data management. It handles the entire
spectrum by providing the basic theory needed and then gradually
introduces the advanced techniques needed to tackle the complex
issues in multimedia content retrieval."
B. Prabhakaran, University of Texas at Dallas
"An excellent and comprehensive resource on multimedia data
management systems, ranging from basic multimedia data- and storage
models to indexing, query and retrieval techniques specifically
adapted to the intricacies of multimedia. This textbook is suited
both for students to gain theoretical insight in the full range of
components required for such a system, or developers who want to
build or improve systems."
Marcel Worring, Intelligent Systems Lab Amsterdam, University of
Amsterdam
This is a very timely book which fills a long felt gap of a
comprehensive textbook possessing depth in the Multimedia
Information Systems area. With a distinctively database systems
perspective, it provides a refreshingly detailed and balanced
treatment of the necessary multimedia content processing
fundamentals. This book can serve as the reference text for senior
undergraduate and graduate courses in Multimedia Information
Systems. It will also be an excellent self-contained take-off point
for beginning researchers in Multimedia Information Retrieval and
Multimedia Databases. Moreover, Multimedia Signal Processing
researchers can use it to gain a solid understanding of the
Database Systems issues."
Mohan S. Kankanhalli, School of Computing, National
University of Singapore
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