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» Majority Based Ranking Approach in Web Image Retrieval
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134
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CVPR
2007
IEEE
16 years 5 months ago
Object retrieval with large vocabularies and fast spatial matching
In this paper, we present a large-scale object retrieval system. The user supplies a query object by selecting a region of a query image, and the system returns a ranked list of i...
James Philbin, Ondrej Chum, Michael Isard, Josef S...
109
Voted
EMNLP
2009
15 years 1 months ago
Improving Web Search Relevance with Semantic Features
Most existing information retrieval (IR) systems do not take much advantage of natural language processing (NLP) techniques due to the complexity and limited observed effectivenes...
Yumao Lu, Fuchun Peng, Gilad Mishne, Xing Wei, Ben...
115
Voted
WWW
2009
ACM
16 years 4 months ago
Learning to tag
Social tagging provides valuable and crucial information for large-scale web image retrieval. It is ontology-free and easy to obtain; however, irrelevant tags frequently appear, a...
Lei Wu, Linjun Yang, Nenghai Yu, Xian-Sheng Hua
134
Voted
SIGIR
2011
ACM
14 years 6 months ago
Parameterized concept weighting in verbose queries
The majority of the current information retrieval models weight the query concepts (e.g., terms or phrases) in an unsupervised manner, based solely on the collection statistics. I...
Michael Bendersky, Donald Metzler, W. Bruce Croft
272
Voted
HT
2011
ACM
14 years 7 months ago
Bridging link and query intent to enhance web search
Understanding query intent is essential to generating appropriate rankings for users. Existing methods have provided customized rankings to answer queries with different intent. W...
Na Dai, Xiaoguang Qi, Brian D. Davison