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...
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...
Many applications in surveillance, monitoring, scientific discovery, and data cleaning require the identification of anomalies. Although many methods have been developed to iden...
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...
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...