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CIKM
2008
Springer
13 years 6 months ago
Learning latent semantic relations from clickthrough data for query suggestion
For a given query raised by a specific user, the Query Suggestion technique aims to recommend relevant queries which potentially suit the information needs of that user. Due to th...
Hao Ma, Haixuan Yang, Irwin King, Michael R. Lyu
KDD
2005
ACM
177views Data Mining» more  KDD 2005»
14 years 5 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
COLING
2010
12 years 11 months ago
Cross-Market Model Adaptation with Pairwise Preference Data for Web Search Ranking
Machine-learned ranking techniques automatically learn a complex document ranking function given training data. These techniques have demonstrated the effectiveness and flexibilit...
Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, ...
CORR
2006
Springer
118views Education» more  CORR 2006»
13 years 4 months ago
Minimally Invasive Randomization for Collecting Unbiased Preferences from Clickthrough Logs
Clickthrough data is a particularly inexpensive and plentiful resource to obtain implicit relevance feedback for improving and personalizing search engines. However, it is well kn...
Filip Radlinski, Thorsten Joachims
WWW
2009
ACM
14 years 5 months ago
A dynamic bayesian network click model for web search ranking
As with any application of machine learning, web search ranking requires labeled data. The labels usually come in the form of relevance assessments made by editors. Click logs can...
Olivier Chapelle, Ya Zhang