Dealing Efficiently with Ontology-Enhanced Linked Data for Multimedia

Oliver Gries, Ralf Möller, Anahita Nafissi, Maurice Rosenfeld, Kamil Sokolski, Sebastian Wandelt

Abstract

In order to provide automatic ontology-based multimedia annotation for producing linked data, scalable high-level media interpretation processes on (video) streams are required. In this paper we shortly describe an abductive media interpretation agent, and based on a Multimedia Content Ontology we introduce partitioning techniques for huge sets of time-related annotation assertions such that interpretation as well as retrieval processes refer to manageable sets of metadata.

Original languageEnglish
Title of host publicationProceedings of the 1st Workshop on High-Level Declarative Stream Processing co-located with the 38th German AI conference (KI 2015), Dresden, Germany, September 22, 2015.
Number of pages14
Volume1447
PublisherCEUR-WS.org
Publication date01.09.2015
Pages28-41
Publication statusPublished - 01.09.2015
Event1st Workshop on High-Level Declarative Stream Processing, HiDeSt 2015 - co-located with the 38th German AI Conference, KI 2015 - Dresden, Germany
Duration: 21.09.201525.09.2015
Conference number: 115610

DFG Research Classification Scheme

  • 409-06 Information Systems, Process and Knowledge Management

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