面向高考语文阅读理解的篇章标题选择研究

关勇,吕国英,李茹,郭少茹,谭红叶

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中文信息学报 ›› 2018, Vol. 32 ›› Issue (6) : 28-35,43.
语言分析与计算

面向高考语文阅读理解的篇章标题选择研究

  • 关勇1,吕国英1,李茹1,2,3,郭少茹1,谭红叶1
作者信息 +

Discourse Title Selection for Chinese Reading Comprehension of College Entrance Examination

  • GUAN Yong1, LV Guoying1, LI Ru1,2,3, GUO Shaoru1, TAN Hongye1
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History +

摘要

高考语文阅读理解篇章标题选择题要求机器根据对篇章内容的理解,从多个候选项中选取能够准确恰当的概括表达篇章内容的选项。标题往往是高度凝练且能准确表达文意、结构鲜明的词串。因此,如何对篇章内容进行归纳概括、对标题结构进行梳理和分析是解答篇章标题选择题的关键。针对该问题,提出了标题与篇章要点相关性分析模型。该模型通过分析标题与篇章要点的相关性,构建了基于标题和篇章要点的相关度矩阵。在此基础上融入标题结构特征,选取与篇章最相关的标题。在全国近10年高考真题和测试题上进行实验,验证了该方法的有效性。

Abstract

Discourse title selection for reading comprehension in the college entrance examination on Chinese is to select the best option by summarizing and analyzing the articles. The title usually captures the meaning of the article accurately in a distinctive structure. Summarizing information about the article and analyzing the title structure is the key to solve the problem. This paper proposes a correlation analysis model based on title and discourse key-points to solve the problem. This model constructs a correlation matrix of title and the discourse key-points, selecting the best answer is jointly with the title structure features. The experiment on the national college entrance examination questions of recent 10 years verifies the validity of the method.

关键词

高考语文 / 阅读理解 / 标题选择 / 神经网络 / 标题结构 / 相关度矩阵

Key words

college entrance examination on Chinese / reading comprehension / title selection / neural network / title structure / correlation matrix

引用本文

导出引用
关勇,吕国英,李茹,郭少茹,谭红叶. 面向高考语文阅读理解的篇章标题选择研究. 中文信息学报. 2018, 32(6): 28-35,43
GUAN Yong, LV Guoying, LI Ru, GUO Shaoru, TAN Hongye. Discourse Title Selection for Chinese Reading Comprehension of College Entrance Examination. Journal of Chinese Information Processing. 2018, 32(6): 28-35,43

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基金

国家863计划(2015AA015407);国家自然科学基金(61772324,61673248)
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