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» A Novel Method for Video Retrieval Using Relevant Feedback
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WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 2 months ago
Learning to rank with multi-aspect relevance for vertical search
Many vertical search tasks such as local search focus on specific domains. The meaning of relevance in these verticals is domain-specific and usually consists of multiple well-d...
Changsung Kang, Xuanhui Wang, Yi Chang, Belle L. T...
CVPR
2008
IEEE
14 years 9 months ago
Utilizing semantic word similarity measures for video retrieval
This is a high level computer vision paper, which employs concepts from Natural Language Understanding in solving the video retrieval problem. Our main contribution is the utiliza...
Yusuf Aytar, Mubarak Shah, Jiebo Luo
TKDE
2008
195views more  TKDE 2008»
13 years 7 months ago
Learning a Maximum Margin Subspace for Image Retrieval
One of the fundamental problems in Content-Based Image Retrieval (CBIR) has been the gap between low-level visual features and high-level semantic concepts. To narrow down this gap...
Xiaofei He, Deng Cai, Jiawei Han
IUI
2009
ACM
14 years 4 months ago
You can play that again: exploring social redundancy to derive highlight regions in videos
Identifying highlights in multimedia content such as video and audio is currently a very difficult technical problem. We present and evaluate a novel algorithm that identifies hig...
Jose San Pedro, Vaiva Kalnikaité, Steve Whi...
KDD
2006
ACM
134views Data Mining» more  KDD 2006»
14 years 7 months ago
Learning to rank networked entities
Several algorithms have been proposed to learn to rank entities modeled as feature vectors, based on relevance feedback. However, these algorithms do not model network connections...
Alekh Agarwal, Soumen Chakrabarti, Sunny Aggarwal