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CIVR
2006
Springer
131views Image Analysis» more  CIVR 2006»
14 years 1 months ago
Exploring the Synergy of Humans and Machines in Extreme Video Retrieval
We introduce an interface for efficient video search that exploits the human ability to quickly scan visual content, after automatic retrieval has arrange the images in expected or...
Alexander G. Hauptmann, Wei-Hao Lin, Rong Yan, Jun...
CIKM
2008
Springer
13 years 12 months ago
Are click-through data adequate for learning web search rankings?
Learning-to-rank algorithms, which can automatically adapt ranking functions in web search, require a large volume of training data. A traditional way of generating training examp...
Zhicheng Dou, Ruihua Song, Xiaojie Yuan, Ji-Rong W...
KDD
2009
ACM
153views Data Mining» more  KDD 2009»
14 years 10 months ago
Predicting bounce rates in sponsored search advertisements
This paper explores an important and relatively unstudied quality measure of a sponsored search advertisement: bounce rate. The bounce rate of an ad can be informally defined as t...
D. Sculley, Robert G. Malkin, Sugato Basu, Roberto...
HT
2009
ACM
14 years 1 months ago
Context-based ranking in folksonomies
With the advent of Web 2.0 tagging became a popular feature. People tag diverse kinds of content, e.g. products at Amazon, music at Last.fm, images at Flickr, etc. Clicking on a t...
Fabian Abel, Matteo Baldoni, Cristina Baroglio, Ni...
WSDM
2012
ACM
267views Data Mining» more  WSDM 2012»
12 years 5 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...