Abstract

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. I. 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.

Original languageEnglish (US)
PublisherCambridge University Press
Number of pages475
ISBN (Electronic)9780511781636
ISBN (Print)9780521887397
DOIs
StatePublished - Jan 1 2011

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Information management
Semantics
Color
Collaborative filtering
Textbooks
Data structures
Textures
Students
Feedback

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Data Management for Multimedia Retrieval. / Candan, Kasim; Sapino, Maria Luisa.

Cambridge University Press, 2011. 475 p.

Research output: Book/ReportBook

Candan, Kasim ; Sapino, Maria Luisa. / Data Management for Multimedia Retrieval. Cambridge University Press, 2011. 475 p.
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