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» Towards content-based relevance ranking for video search
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MM
2006
ACM
181views Multimedia» more  MM 2006»
13 years 10 months ago
Towards content-based relevance ranking for video search
Most existing web video search engines index videos by file names, URLs, and surrounding texts. These types of video roughly describe the whole video in an abstract level without ...
Wei Lai, Xian-Sheng Hua, Wei-Ying Ma
MTA
2002
166views more  MTA 2002»
13 years 4 months ago
MUSE: A Content-Based Image Search and Retrieval System Using Relevance Feedback
ThefieldofContent-BasedVisualInformationRetrieval(CBVIR)hasexperiencedtremendousgrowth in the recent years and many research groups are currently working on solutions to the proble...
Oge Marques, Borko Furht
ICMCS
2005
IEEE
134views Multimedia» more  ICMCS 2005»
13 years 10 months ago
Relevance Feedback Methods in Content Based Retrieval and Video Summarization
In the current state-of-the-art in multimedia content analysis (MCA), the fundamental techniques are typically derived from core pattern recognition and computer vision algorithms...
Micha Haas, Ard Oerlemans, Michael S. Lew
SEMWEB
2009
Springer
13 years 11 months ago
Towards Lightweight and Robust Large Scale Emergent Knowledge Processing
We present a lightweight framework for processing uncertain emergent knowledge that comes from multiple resources with varying relevance. The framework is essentially RDF-compatibl...
Vít Novácek, Stefan Decker
MIR
2010
ACM
163views Multimedia» more  MIR 2010»
13 years 6 months ago
SNDocRank: a social network-based video search ranking framework
Multimedia ranking algorithms are usually user-neutral and measure the importance and relevance of documents by only using the visual contents and meta-data. However, users’ int...
Liang Gou, Hung-Hsuan Chen, Jung-Hyun Kim, Xiaolon...