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 language | English |
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Title of host publication | Proceedings 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 pages | 14 |
Volume | 1447 |
Publisher | CEUR-WS.org |
Publication date | 01.09.2015 |
Pages | 28-41 |
Publication status | Published - 01.09.2015 |
Event | 1st Workshop on High-Level Declarative Stream Processing, HiDeSt 2015 - co-located with the 38th German AI Conference, KI 2015 - Dresden, Germany Duration: 21.09.2015 → 25.09.2015 Conference number: 115610 |
DFG Research Classification Scheme
- 409-06 Information Systems, Process and Knowledge Management