Book contents
- Frontmatter
- Contents
- Preface
- 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, and 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
- Bibliography
- Index
- Plate section
Preface
Published online by Cambridge University Press: 05 July 2014
- Frontmatter
- Contents
- Preface
- 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, and 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
- Bibliography
- Index
- Plate section
Summary
Database and multimedia systems emerged to address the needs of very different application domains. New applications (such as digital libraries, increasingly dynamic and complex web content, and scientific data management), on the other hand, necessitate a common understanding of both of these disciplines. Consequently, as these domains matured over the years, their respective scientific disciplines moved closer. On the media management side, researchers have been concentrating on media-content description and indexing issues as part of the MPEG7 and other standards. On the data management side, commercial database management systems, which once primarily targeted traditional business applications, today focus on media and heterogeneous-data intensive applications, such as digital libraries, integrated database/information-retrieval systems, sensor networks, bioinformatics, e-business applications, and of course the web.
There are three reasons for the heterogeneity inherent in multimedia applications and information management systems. First, the semantics of the information captured in different forms can be drastically different from each other. Second, resource and processing requirements of various media differ substantially. Third, the user and context have significant impacts on what information is relevant and how it should be processed and presented. A key observation, on the other hand, is that rather than being independent, the challenges associated with the semantic, resource, and context-related heterogeneities are highly related and require a common understanding and unified treatment within a multimedia data management system (MDMS). Consequently, internally a multimedia database management system looks and functions differently than a traditional (relational, object-oriented, or even XML) DBMS.
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- Data Management for Multimedia Retrieval , pp. ix - xPublisher: Cambridge University PressPrint publication year: 2010