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| 基于似然损失函数的组样本排序学习方法* | |
| 引用本文： | 林原,徐博,孙晓玲,林鸿飞,许侃.基于似然损失函数的组样本排序学习方法*[J].模式识别与人工智能,2017,30(3):235-241. |
| 作者姓名： | 林原 徐博 孙晓玲 林鸿飞 许侃 |
| 作者单位： | 1.大连理工大学 人文与社会科学学部 大连 116024 2.大连理工大学 计算机科学与技术学院 大连 116024 |
| 基金项目： | 国家自然科学基金项目(No.61602078,61572102,61402075,61277370)、中国博士后科学基金项目(No.2016T90224,2015M581337)、中央高校基本科研业务费专项资金(No.DUT15RW401)资助 |
| 摘 要： | 组样本用于模型训练,为排序学习方法的构造提供一种新的思路.文中改进已有的组样本排序学习方法,构造组样本损失函数,用于排序学习模型的训练.基于似然损失函数,采用样本偏序权重损失函数和最优初始序列选择方法,构造基于神经网络的组排序学习方法,实验证明文中方法能够有效提高排序准确率. |
| 关 键 词： | 组样本 信息检索 排序学习 |
| 收稿时间： | 2016-11-10 |
Group Sample Learning to Rank Approach Based on Likelihood Loss Function |
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| LIN Yuan,XU Bo,SUN Xiaoling,LIN Hongfei,XU Kan.Group Sample Learning to Rank Approach Based on Likelihood Loss Function[J].Pattern Recognition and Artificial Intelligence,2017,30(3):235-241. | |
| Authors: | LIN Yuan XU Bo SUN Xiaoling LIN Hongfei XU Kan |
| Affiliation: | 1.Faculty of Humanities and Social Sciences, Dalian University of Technology, Dalian 116024 2.School of Computer Science and Technology, Dalian University of Technology, Dalian 116024 |
| Abstract: | Group sample used for training the ranking model provides a new idea to construct learning to rank methods. In this paper, the new loss function is constructed for group samples to train the learning to rank model. The preference-weighted loss function and the initial ranking list optimization are employed to construct a new group learning to rank method based on neural network. Experimental results show that the proposed approach is effective in improving ranking performance. |
| Keywords: | Group Sample Information Retrieval Learning to Rank |
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