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Presentation
On Domain Similarity and Effectiveness of Adapting-to-Rank
Proceedings of the 18th ACM Conference on Information and Knowledge Management
  • Keke Chen, Wright State University - Main Campus
  • Jing Bai
  • Srihari Reddy
  • Belle Tseng
Document Type
Conference Proceeding
Publication Date
11-1-2009
Catalog Record
Catalog Record
Abstract
Adapting 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.
Comments

Presented at the 18th ACM Conference on Information and Knowledge Management, Hong Kong, China, November 2-6, 2009.

Citation Information
Keke 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/