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» Diverse Active Ranking for Multimedia Search
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CVPR
2007
IEEE
13 years 8 months ago
Diverse Active Ranking for Multimedia Search
Interactively learning from a small sample of unlabeled examples is an enormously challenging task, one that often arises in vision applications. Relevance feedback and more recen...
ShyamSundar Rajaram, Charlie K. Dagli, Nemanja Pet...
WWW
2010
ACM
13 years 11 months ago
Actively predicting diverse search intent from user browsing behaviors
This paper is concerned with actively predicting search intent from user browsing behavior data. In recent years, great attention has been paid to predicting user search intent. H...
Zhicong Cheng, Bin Gao, Tie-Yan Liu
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...
MIR
2006
ACM
129views Multimedia» more  MIR 2006»
13 years 10 months ago
Diversity in multimedia information retrieval research
Multimedia information retrieval is a highly diverse field. A variety of data types, research problems, methodologies are involved. Researchers in the field come from very diff...
James Ze Wang, Nozha Boujemaa, Alberto Del Bimbo, ...
ICMCS
2008
IEEE
141views Multimedia» more  ICMCS 2008»
13 years 11 months ago
Ranking music data by relevance and importance
Due to the rapidly increasing availability of audio files on the Web, it is relevant to augment search engines with advanced audio search functionality. In this context, the rank...
Maria M. Ruxanda, Alexandros Nanopoulos, Christian...