Selecting optimal training data for learning to rank

doi:10.1016/j.ipm.2011.01.002

	Selecting optimal training data for learning to rank
	Geng, Xiubo 1; Qin, Tao 2; Liu, Tie-Yan 2; Cheng, Xue-Qi 1; Li, Hang 2
	2011-09-01
发表期刊	INFORMATION PROCESSING & MANAGEMENT
ISSN	0306-4573
卷号	47 期号:5 页码:730-741
摘要	This paper is concerned with the quality of training data in learning to rank for information retrieval. While many data selection techniques have been proposed to improve the quality of training data for classification, the study on the same issue for ranking appears to be insufficient. As pointed out in this paper, it is inappropriate to extend technologies for classification to ranking, and the development of novel technologies is sorely needed. In this paper, we study the development of such technologies. To begin with, we propose the concept of "pairwise preference consistency" (PPC) to describe the quality of a training data collection from the ranking point of view. PPC takes into consideration the ordinal relationship between documents as well as the hierarchical structure on queries and documents, which are both unique properties of ranking. Then we select a subset of the original training documents, by maximizing the PPC of the selected subset. We further propose an efficient solution to the maximization problem. Empirical results on the LETOR benchmark datasets and a web search engine dataset show that with the subset of training data selected by our approach, the performance of the learned ranking model can be significantly improved. (C) 2011 Elsevier Ltd. All rights reserved.
关键词	Learning to rank Selecting optimal training data
DOI	10.1016/j.ipm.2011.01.002
收录类别	SCI
语种	英语
WOS研究方向	Computer Science ; Information Science & Library Science
WOS类目	Computer Science, Information Systems ; Information Science & Library Science
WOS记录号	WOS:000294087400010
出版者	PERGAMON-ELSEVIER SCIENCE LTD
引用统计	被引频次：9[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/12747
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Geng, Xiubo
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China 2.Microsoft Res Asia, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Geng, Xiubo,Qin, Tao,Liu, Tie-Yan,et al. Selecting optimal training data for learning to rank[J]. INFORMATION PROCESSING & MANAGEMENT,2011,47(5):730-741.
APA	Geng, Xiubo,Qin, Tao,Liu, Tie-Yan,Cheng, Xue-Qi,&Li, Hang.(2011).Selecting optimal training data for learning to rank.INFORMATION PROCESSING & MANAGEMENT,47(5),730-741.
MLA	Geng, Xiubo,et al."Selecting optimal training data for learning to rank".INFORMATION PROCESSING & MANAGEMENT 47.5(2011):730-741.