Los Angeles, CA
March 31, 2009 to April 2, 2009
This paper presents an overview of learning to rank. It includes three parts: related concepts including the definitions of ranking and learning to rank; a summary of pointwise models, pairwise models, and listwise models; estimation measures such as Normalized Discount Cumulative Gain and Mean Average Precision, respectively. Considering the deficiency that current learning to rank models lack of continual learning ability, we present a new continual learning idea that combines multi-agent autonomy learning mechanism with molecular immune mechanism for ranking.
Xishuang Dong, Xiaodong Chen, Yi Guan, Zhiming Yu, Sheng Li, "An Overview of Learning to Rank for Information Retrieval", CSIE, 2009, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE, 2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, pp. 600-606, doi:10.1109/CSIE.2009.1090