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Ontology and Sequential Rule Based Streaming Media Event Recognition
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  • Journal title : Journal of KIISE
  • Volume 43, Issue 4,  2016, pp.470-479
  • Publisher : Korean Institute of Information Scientists and Engineers
  • DOI : 10.5626/JOK.2016.43.4.470
 Title & Authors
Ontology and Sequential Rule Based Streaming Media Event Recognition
Soh, Chi-Seung; Park, Hyun-Kyu; Park, Young-Tack;
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As the number of various types of media data such as UCC (User Created Contents) increases, research is actively being carried out in many different fields so as to provide meaningful media services. Amidst these studies, a semantic web-based media classification approach has been proposed; however, it encounters some limitations in video classification because of its underlying ontology derived from meta-information such as video tag and title. In this paper, we define recognized objects in a video and activity that is composed of video objects in a shot, and introduce a reasoning approach based on description logic. We define sequential rules for a sequence of shots in a video and describe how to classify it. For processing the large amount of increasing media data, we utilize Spark streaming, and a distributed in-memory big data processing framework, and describe how to classify media data in parallel. To evaluate the efficiency of the proposed approach, we conducted an experiment using a large amount of media ontology extracted from Youtube videos.
streaming;reasoning;media ontology;distributed system;event recognition;
 Cited by
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