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WSDM
2009
ACM
191views Data Mining» more  WSDM 2009»
15 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...
WSDM
2009
ACM
178views Data Mining» more  WSDM 2009»
15 years 11 months ago
User Browsing Graph: Structure, Evolution and Application
This paper focuses on ‘user browsing graph’ which is constructed with users’ click-through behavior modeled with Web access logs. User browsing graph has recently been adopt...
Yiqun Liu, Min Zhang, Shaoping Ma, Liyun Ru
KDD
2009
ACM
193views Data Mining» more  KDD 2009»
15 years 11 months ago
Category detection using hierarchical mean shift
Many applications in surveillance, monitoring, scientific discovery, and data cleaning require the identification of anomalies. Although many methods have been developed to iden...
Pavan Vatturi, Weng-Keen Wong
KDD
2009
ACM
210views Data Mining» more  KDD 2009»
15 years 11 months ago
Modeling and predicting user behavior in sponsored search
Implicit user feedback, including click-through and subsequent browsing behavior, is crucial for evaluating and improving the quality of results returned by search engines. Severa...
Josh Attenberg, Sandeep Pandey, Torsten Suel
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
15 years 11 months ago
Primal sparse Max-margin Markov networks
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
Jun Zhu, Eric P. Xing, Bo Zhang
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