Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Adapting ranking SVM to document retrieval
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
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We propose an approach QRRS (Query Relaxative Ranking SVM) that divides a ranking function into different relaxation steps, so that only cheap features are used in Ranking SVM of early steps for query efficiency. We show search quality in the approach is improved compared to conventional Ranking SVM.