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2009 WRI World Congress on Computer Science and Information Engineering
An Overview of Learning to Rank for Information Retrieval
Los Angeles, California USA
March 31-April 02
ISBN: 978-0-7695-3507-4
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.
Citation:
Xishuang Dong, Xiaodong Chen, Yi Guan, Zhiming Yu, Sheng Li, "An Overview of Learning to Rank for Information Retrieval," csie, vol. 3, pp.600-606, 2009 WRI World Congress on Computer Science and Information Engineering, 2009
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