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论文类型： 会议论文

发表时间： 2011-07-24

收录刊物： EI、Scopus

页面范围： 1091-1092

摘要： In this paper, we use query-level regression as the loss function. The regression loss function has been used in pointwise methods, however pointwise methods ignore the query boundaries and treat the data equally across queries, and thus the effectiveness is limited. We show that regression is an effective loss function for learning to rank when used in query-level. We propose a method, namely ListReg, to use neural network to model the ranking function and gradient descent for optimization. Experimental results show that ListReg significantly outperforms pointwise Regression and the state-of-the-art listwise method in most cases.