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» Online learning to diversify from implicit feedback
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ICML
2009
IEEE
14 years 7 months ago
Interactively optimizing information retrieval systems as a dueling bandits problem
We present an on-line learning framework tailored towards real-time learning from observed user behavior in search engines and other information retrieval systems. In particular, ...
Yisong Yue, Thorsten Joachims
CORR
2006
Springer
126views Education» more  CORR 2006»
13 years 6 months ago
Evaluating the Robustness of Learning from Implicit Feedback
This paper evaluates the robustness of learning from implicit feedback in web search. In particular, we create a model of user behavior by drawing upon user studies in laboratory ...
Filip Radlinski, Thorsten Joachims
WWW
2007
ACM
14 years 7 months ago
Summarization of online image collections via implicit feedback
The availability of map interfaces and location-aware devices makes a growing amount of unstructured, geo-referenced information available on the Web. In particular, over twelve m...
Shane Ahern, Simon King, Mor Naaman, Rahul Nair
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 7 months ago
Query chains: learning to rank from implicit feedback
This paper presents a novel approach for using clickthrough data to learn ranked retrieval functions for web search results. We observe that users searching the web often perform ...
Filip Radlinski, Thorsten Joachims
COMPUTER
2007
107views more  COMPUTER 2007»
13 years 6 months ago
Search Engines that Learn from Implicit Feedback
Thorsten Joachims, Filip Radlinski