On Domain Similarity and Effectiveness of Adapting-to-RankProceedings of the 18th ACM Conference on Information and Knowledge Management
Document TypeConference Proceeding
AbstractAdapting to rank address the problem of insufficient domain-specific labeled training data in learning to rank. However, the initial study show 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 measures: relevance correlation and sample distribution correlation.
Citation InformationKeke Chen, Jing Bai, Srihari Reddy and Belle Tseng. "On Domain Similarity and Effectiveness of Adapting-to-Rank" Proceedings of the 18th ACM Conference on Information and Knowledge Management (2009) p. 1601 - 1604 ISSN: 9781605585123
Available at: http://works.bepress.com/keke_chen/26/