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WSDM
2009
ACM
191views Data Mining» more  WSDM 2009»
13 years 11 months ago
Generating labels from clicks
The ranking function used by search engines to order results is learned from labeled training data. Each training point is a (query, URL) pair that is labeled by a human judge who...
Rakesh Agrawal, Alan Halverson, Krishnaram Kenthap...
WINE
2005
Springer
136views Economy» more  WINE 2005»
13 years 10 months ago
Click Fraud Resistant Methods for Learning Click-Through Rates
Abstract. In pay-per-click online advertising systems like Google, Overture, or MSN, advertisers are charged for their ads only when a user clicks on the ad. While these systems ha...
Nicole Immorlica, Kamal Jain, Mohammad Mahdian, Ku...
SIGIR
2008
ACM
13 years 4 months ago
Learning query intent from regularized click graphs
This work presents the use of click graphs in improving query intent classifiers, which are critical if vertical search and general-purpose search services are to be offered in a ...
Xiao Li, Ye-Yi Wang, Alex Acero
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
NAACL
2010
13 years 2 months ago
Learning Dense Models of Query Similarity from User Click Logs
The goal of this work is to integrate query similarity metrics as features into a dense model that can be trained on large amounts of query log data, in order to rank query rewrit...
Fabio De Bona, Stefan Riezler, Keith Hall, Massimi...