IR evaluation methods for retrieving highly relevant documents
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
A regression framework for learning ranking functions using relative relevance judgments
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Trada: tree based ranking function adaptation
Proceedings of the 17th ACM conference on Information and knowledge management
Learning to rank only using training data from related domain
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Cross-market model adaptation with pairwise preference data for web search ranking
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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Adapting to rank address the problem of insufficient domain-specific labeled training data in learning to rank. However, the initial study shows that adaptation is not always effective. In this paper, we investigate the relationship between the domain similarity and the effectiveness of domain adaptation with the help of two domain similarity measure: relevance correlation and sample distribution correlation.