Institute of Computing Technology, Chinese Academy IR
Learning multiple metrics for ranking | |
Geng, Xiubo; Cheng, Xue-Qi | |
2011-09-01 | |
发表期刊 | FRONTIERS OF COMPUTER SCIENCE IN CHINA |
ISSN | 1673-7350 |
卷号 | 5期号:3页码:259-267 |
摘要 | Directly optimizing an information retrieval (IR) metric has become a hot topic in the field of learning to rank. Conventional wisdom believes that it is better to train for the loss function on which will be used for evaluation. But we often observe different results in reality. For example, directly optimizing averaged precision achieves higher performance than directly optimizing precision@3 when the ranking results are evaluated in terms of precision@3. This motivates us to combine multiple metrics in the process of optimizing IR metrics. For simplicity we study learning with two metrics. Since we usually conduct the learning process in a restricted hypothesis space, e.g., linear hypothesis space, it is usually difficult to maximize both metrics at the same time. To tackle this problem, we propose a relaxed approach in this paper. Specifically, we incorporate one metric within the constraint while maximizing the other one. By restricting the feasible hypothesis space, we can get a more robust ranking model. Empirical results on the benchmark data set LETOR show that the relaxed approach is superior to the direct linear combination approach, and also outperforms other baselines. |
关键词 | learning to rank multiple measures direct optimization |
DOI | 10.1007/s11704-011-0152-5 |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods |
WOS记录号 | WOS:000293638400001 |
出版者 | HIGHER EDUCATION PRESS |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.204/handle/2XEOYT63/13234 |
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 | Chinese Acad Sci, Inst Comp Technol, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Geng, Xiubo,Cheng, Xue-Qi. Learning multiple metrics for ranking[J]. FRONTIERS OF COMPUTER SCIENCE IN CHINA,2011,5(3):259-267. |
APA | Geng, Xiubo,&Cheng, Xue-Qi.(2011).Learning multiple metrics for ranking.FRONTIERS OF COMPUTER SCIENCE IN CHINA,5(3),259-267. |
MLA | Geng, Xiubo,et al."Learning multiple metrics for ranking".FRONTIERS OF COMPUTER SCIENCE IN CHINA 5.3(2011):259-267. |
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