面向框架语义分析的目标词自动识别方法

doi:10.6040/j.issn.1671-9352.3.2014.076

山东大学学报（理学版） ›› 2015, Vol. 50 ›› Issue (07): 45-53.doi: 10.6040/j.issn.1671-9352.3.2014.076

面向框架语义分析的目标词自动识别方法

陈亚东, 洪宇, 杨雪蓉, 王潇斌, 姚建民, 朱巧明

苏州大学计算机科学与技术学院, 江苏苏州 215006

收稿日期:2015-03-05 出版日期:2015-07-20 发布日期:2015-07-31
通讯作者: 洪宇(1978-),男,副教授,主要研究领域为话题检测、信息检索和信息抽取.E-mail:tianxianer@gmail.com E-mail:tianxianer@gmail.com
作者简介:陈亚东(1990-),男,硕士研究生,主要研究领域为信息抽取.E-mail:chinachenyadong@gmail.com
基金资助:
国家自然科学基金资助项目(61373097, 61272259, 61272260)

Automatic target identification in frame semantic parsing

CHEN Ya-dong, HONG Yu, YANG Xue-rong, WANG Xiao-bin, YAO Jian-min, ZHU Qiao-ming

School of Computer Science and Technology, Soochow University, Suzhou 215006, Jiangsu, China

Received:2015-03-05 Online:2015-07-20 Published:2015-07-31

摘要/Abstract

摘要： 提出了一种基于监督学习的目标词自动识别方法,分析并检验了多种区分目标词、框架元素和非实义词的分类特征,并在此基础上,联合使用监督学习与规则匹配方法,形成了兼顾扩展性和精确性的目标词识别系统。在FrameNet语料集的实验结果显示,融合方法的目标词识别获得了3.86%的性能提升。

关键词: 框架语义, 目标词识别, 监督学习, 框架目标词

Abstract: An automatic target identification method is introduced by analyzing some classification features to distinguish target words, frame elements and non-substantive words. A scalable and accurate target identification system is obtained. The experiment results on FrameNet prove that the joint method gains 3.86% in target identification.

Key words: frame semantics, target identification, supervised learning, frame target

中图分类号:

TP391

陈亚东, 洪宇, 杨雪蓉, 王潇斌, 姚建民, 朱巧明. 面向框架语义分析的目标词自动识别方法[J]. 山东大学学报（理学版）, 2015, 50(07): 45-53.

CHEN Ya-dong, HONG Yu, YANG Xue-rong, WANG Xiao-bin, YAO Jian-min, ZHU Qiao-ming. Automatic target identification in frame semantic parsing[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2015, 50(07): 45-53.

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面向框架语义分析的目标词自动识别方法

Automatic target identification in frame semantic parsing

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