Journal
KNOWLEDGE-BASED SYSTEMS
Volume 108, Issue -, Pages 102-109Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2016.05.022
Keywords
Multimedia summarization; Semantics analysis; Sentics analysis; Multimodal analysis; Multimedia-related services
Categories
Funding
- Singapore's Ministry of Education (MOE) [T1 251RES1415]
- JSPS [16K16058]
- Grants-in-Aid for Scientific Research [16K16058] Funding Source: KAKEN
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The rapid growth in the amount of user-generated content (UGCs) online necessitates for social media companies to automatically extract knowledge structures (concepts) from photos and videos to provide diverse multimedia-related services. However, real-world photos and videos are complex and noisy, and extracting semantics and sentics from the multimedia content alone is a very difficult task because suitable concepts may be exhibited in different representations. Hence, it is desirable to analyze UGCs from multiple modalities for a better understanding. To this end, we first present the EventBuilder system that deals with semantics understanding and automatically generates a multimedia summary for a given event in real-time by leveraging different social media such as Wikipedia and Flickr. Subsequently, we present the EventSensor system that aims to address sentics understanding and produces a multimedia summary for a given mood. It extracts concepts and mood tags from visual content and textual metadata of UGCs, and exploits them in supporting several significant multimedia-related services such as a musical multimedia summary. Moreover, EventSensor supports sentics-based event summarization by leveraging EventBuilder as its semantics engine component. Experimental results confirm that both Event Builder and EventSensor outperform their baselines and efficiently summarize knowledge structures on the YFCC100M dataset. (C) 2016 Elsevier B.V. All rights reserved.
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