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EMMA – A Formal Basis for Querying Enhanced Multimedia Meta Objects

  • Sonja Zillner
  • Werner Winiwarter
Conference paper
  • 695 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3730)

Abstract

Today’s multimedia content formats primarily encode the presentation of content but not the information the content conveys. However, this presentation-oriented modeling only permits the inflexible, hard-wired presentation of multimedia content. For the realization of advanced operations like the retrieval and reuse of content, automatic composition, or adaptation to a user’s needs, the multimedia content has to be enriched by additional semantic information, e.g. the semantic interrelationships between single multimedia content items. Enhanced Multimedia Meta Objects (EMMOs) are a novel approach to multimedia content modeling, which combines media, semantic relationships between those media, as well as functionality on the media (such as rendering) into tradeable and versionable knowledge-enriched units of multimedia content. For the processing of EMMOs and the knowledge they incorporate, suitable querying facilities are required. Based on the formal definition of the EMMO model, in this paper, we propose and formally define the EMMO Algebra EMMA, a query algebra that is adequate and complete with regard to the EMMO model. EMMA offers a rich set of orthogonal query operators, which are sufficiently expressive to provide access to all aspects of EMMOs and enable efficient query rewriting and optimization. In addition, they allow for the seamless integration of ontological knowledge within queries, such as supertype/subtype relationships, transitive and inverse associations, etc. Thus, EMMA represents a sound and adequate foundation for the realization of powerful EMMO querying facilities. We have finished the implementation of an EMMO container environment and an EMMA query execution engine, and are currently in the process of evaluating the query algebra in several case studies.

Keywords

Resource Description Framework Multimedia Content Media Object Semantic Aspect Navigation Path 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sonja Zillner
    • 1
  • Werner Winiwarter
    • 1
  1. 1.Faculty of Computer ScienceUniversity of ViennaVienna

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