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WWW
2007
ACM
16 years 7 months ago
Predicting clicks: estimating the click-through rate for new ads
Search engine advertising has become a significant element of the Web browsing experience. Choosing the right ads for the query and the order in which they are displayed greatly a...
Matthew Richardson, Ewa Dominowska, Robert Ragno
SIGIR
2012
ACM
13 years 9 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
MCI
2001
15 years 8 months ago
In a Strange Land: modelling and understanding cyberspace
: This paper begins with a long-term view of the development of cyberspace. This includes a brief examination of the worldview of a 16th-century mapmaker and over 4000 years of dev...
Alan J. Dix
CIKM
2008
Springer
15 years 8 months ago
Trada: tree based ranking function adaptation
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions for different search domains, ...
Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, La...
ICVS
1999
Springer
15 years 11 months ago
Action Reaction Learning: Automatic Visual Analysis and Synthesis of Interactive Behaviour
We propose Action-Reaction Learning as an approach for analyzing and synthesizing human behaviour. This paradigm uncovers causal mappings between past and future events or between...
Tony Jebara, Alex Pentland