基于协同训练的文本蕴含识别

被引：1

作者：

任函 ^{[1
]}

万菁 ^{[2
]}

吴泓缈 ^{[1
,2
]}

冯文贺 ^{[3
]}

机构：

[1] 武汉大学外国语言文学学院

[2] 武汉大学湖北省语言与智能信息处理研究基地

[3] 武汉大学计算机学院

来源：

中文信息学报 | 2014年 / 06期

基金：

中国博士后科学基金;

关键词：

文本蕴含识别; 协同训练; 语义树核;

D O I：

暂无

中图分类号：

TP391.1 [文字信息处理];

学科分类号：

081203 ; 0835 ;

摘要：

针对文本蕴含的训练数据不足的问题,该文提出了基于协同训练的文本蕴含识别方法。该方法利用少量已标注的蕴含数据和大量未标注数据进行协同训练。为此,该文利用改写视图和评估视图,从结构和非结构两个角度考察蕴含关系,并将语义树核分类器和基于统计特征的分类器应用于两个视图,同时利用协同训练的结果训练一个综合分类器,用于对新数据进行预测。实验表明,基于协同训练的蕴含识别方法能在少量训练数据的情况下获得较好的识别性能。

引用

页码：114 / 119

页数：6

共 12 条

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