计算机科学 ›› 2021, Vol. 48 ›› Issue (11A): 124-129.doi: 10.11896/jsjkx.210100226

• 智能计算 • 上一篇    下一篇

基于规则的有标复句关系的自动识别

杨进才1, 胡巧玲1, 胡泉2   

  1. 1 华中师范大学计算机学院 武汉430079
    2 华中师范大学人工智能教育学部 武汉430079
  • 出版日期:2021-11-10 发布日期:2021-11-12
  • 通讯作者: 杨进才(jcyang@mail.ccnu.edu.cn)
  • 基金资助:
    国家社科基金(19BYY092)

Rule-based Automatic Recognition of Relations for Marked Complex Sentences

YANG Jin-cai1, HU Qiao-ling1, HU Quan2   

  1. 1 School of Computer,Central China Normal University,Wuhan 430079,China
    2 Faculty of Artificial Intelligence in Education,Central China Normal University,Wuhan 430079,China
  • Online:2021-11-10 Published:2021-11-12
  • About author:YANG Jin-cai,born in 1967,doctor,professor,doctoral supervisor,is a member of China Computer Federation.His main research interests include modern database and information system,Chinese information processing,artificial intelligence and natural language processing.
  • Supported by:
    National Social Science Fundation of China(19BYY092).

摘要: 汉语复句的语义表达复杂,复句关系分类问题作为汉语篇章研究与应用的重要内容,一直是自然语言处理领域关注的热点。文中总结与挖掘出复句类别自动识别的十几类字面、句法特征,将特征形式化为规则,用关系词触发规则的机制,对有标复句进行十二类关系类别的识别。实验结果表明该方法取得了较高的准确率,优于现有的方法。

关键词: 复句关系分类, 规则, 有标复句, 自动识别

Abstract: Semantic expression of Chinese complex sentences is complicated.As an important content of Chinese discourse studies,complex sentences classification has always been a hot spot in the field of natural language processing.This paper summarizes and excavates more than ten types of literal and syntactic features for automatic identification of complex sentence categories,formalizes the features and constitutes rules,and uses the mechanism of relational words to trigger the rules to identify twelve types of relationship categories for marked complex sentences.Experimental results show that this method has achieved a higher accuracy rate,which is better than the existing methods.

Key words: Automatic recognition, Complex sentence classification, Marked complex sentences, Rules

中图分类号: 

  • TP391
[1]LIU Y,LI S,ZHANG X,et al.Implicit discourse relation classification via multi-task neural networks[C]//Proceedings of the AAAI Conference on Artificial Intelligence.2016.
[2]ZOU B,ZHOU G,ZHU Q.Negation focus identification withcontextual discourse information[C]//Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1:Long Papers).2014:522-530.
[3]LIAKATA M,DOBNIK S,SAHA S,et al.A discourse-driven content model for summarising scientific articles evaluated in a complex question answering task[C]//Proceedings of the 2013 Conference on Empirical Methods in Natural Language Proces-sing.2013:747-757.
[4]PAPINENI K.BLEU:A method for automatic evaluation of machine translation [C]//Proceedings of the 40 th Annual Meeting of the Association for Computational Linguistics (ACL).2002.
[5]XING F Y.Research on Chinese Complex Sentences[M].Beijing:The Commercial Press,2001:1-37.
[6]HU J Z,SHU J B,HU Q,et al.Research on the expressionmethod of rules in the automatic recognition of relative words in complex sentences[J].Computer Engineering and Applications,2016,52(1):127-132.
[7]HU J Z,SHU J B,HU Q,et al.Research on the Restrictive Conditions of Rules in the Automatic Recognition of Relative Words in Chinese Complex Sentences[J].Language and Writing Applications,2015(1):82-89.
[8]HU J Z,HU Q,SHU J B.Research on Inclusion Matching Algorithm of Rule Analysis in Automatic Recognition of Relative Words in Complex Sentences[J].Journal of Central China Normal University (Natural Science Edition),2014,48(5):643-649.
[9]JIA S M,LEI L L,HU M S.Rule-based automatic identification of relative words in complex sentences[J].Journal of Chinese Information Processing,2015,29(1):44-48,66.
[10]LI Y C,SUN J,ZHOU G D,et al.Research on Recognition and Classification of Relative Words in Complex Sentences Based on Tsinghua Chinese Treebank[J].Journal of Peking University (Natural Sciences Edition),2014,50(1):118-124.
[11]HU J Z,CHEN J M,YANG J C,et al.Research on Automatic Marking of Joint Relation Marking Based on Rules[J].ComputerScience,2012,39(7):190-194.
[12]YANG J C,XIE F,WANG Z H,et al.Conflict Detection and Processing in the Rule Generation System of Complex Sentence Relative Words[J].Journal of Chinese Information Processing,2015,29(4):8-15.
[13]YANG J C,XIE F,HU J Z.Research on Rule Engine in Automatic Identification of Relative Words in Chinese Complex Sentences[J].Computer Science,2014,41(S2):25-28.
[14]YANG J C,GUO K K,SHEN X J,et al.Automatic recognition and rule mining of complex sentences based on Bayesian model[J].Computer Science,2015,42(7):291-294,319.
[15]HUANG H H,CHANG T W,CHEN H Y,et al.Interpretation of Chinese discourse connectives for explicit discourse relation recognition[C]//The 25th International Conference on Computational Linguistics:Technical Papers(COLING 2014).2014:632-643.
[16]HUANG H H,CHEN H H.Contingency and comparison relation labeling and structure prediction in Chinese sentences[C]//Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue.2012:261-269.
[17]YANG J C,CHEN Z Z,SHEN X J,et al.Automatic identification of the relational category of marked complex sentences in the non-filling state of two sentences[J].Application Research of Computers,2017,34(10):2950-2953.
[18]YANG J C,WANG Y Y,CAO Y,et al.Feature fusion CNN relation recognition method of relative words non-filled complex sentences[J].Computer Systems & Applications,2020,29(6):224-229.
[19]SUN K L,DENG Z H,LI Y,et al.Recognition of Chinese Complex Sentence Relations Based on Multi-channel CNN Based on In-Sentence Attention Mechanism[J].Journal of Chinese Information Processing,2020,34(6):9-17,26.
[20]LAI S,XU L,LIU K,et al.Recurrent convolutional neural networks for text classification[C]//Twenty-ninth AAAI Conference on Artificial Intelligence.2015.
[1] 张露萍, 徐飞.
具有突触规则的脉冲神经膜系统综述
Survey on Spiking Neural P Systems with Rules on Synapses
计算机科学, 2022, 49(8): 217-224. https://doi.org/10.11896/jsjkx.220300078
[2] 李瑭, 秦小麟, 迟贺宇, 费珂.
面向多无人系统的安全协同模型
Secure Coordination Model for Multiple Unmanned Systems
计算机科学, 2022, 49(7): 332-339. https://doi.org/10.11896/jsjkx.210600107
[3] 郁舒昊, 周辉, 叶春杨, 王太正.
SDFA:基于多特征融合的船舶轨迹聚类方法研究
SDFA:Study on Ship Trajectory Clustering Method Based on Multi-feature Fusion
计算机科学, 2022, 49(6A): 256-260. https://doi.org/10.11896/jsjkx.211100253
[4] 曹扬晨, 朱国胜, 孙文和, 吴善超.
未知网络攻击识别关键技术研究
Study on Key Technologies of Unknown Network Attack Identification
计算机科学, 2022, 49(6A): 581-587. https://doi.org/10.11896/jsjkx.210400044
[5] 张耕强, 谢钧, 杨章林.
FDSR:一种面向SD-MANET的快速转发规则下发方法
Accelerating Forwarding Rules Issuance with Fast-Deployed-Segment-Routing(FDSR) in SD-MANET
计算机科学, 2022, 49(2): 377-382. https://doi.org/10.11896/jsjkx.210800045
[6] 刘小蝶.
基于边界感知的复杂名词短语的识别和转换研究
Recognition and Transformation for Complex Noun Phrases Based on Boundary Perception
计算机科学, 2021, 48(6A): 299-305. https://doi.org/10.11896/jsjkx.200500157
[7] 徐慧慧, 晏华.
基于相对危险度的儿童先心病风险因素分析算法
Relative Risk Degree Based Risk Factor Analysis Algorithm for Congenital Heart Disease in Children
计算机科学, 2021, 48(6): 210-214. https://doi.org/10.11896/jsjkx.200500082
[8] 沈夏炯, 杨继勇, 张磊.
基于不相关属性集合的属性探索算法
Attribute Exploration Algorithm Based on Unrelated Attribute Set
计算机科学, 2021, 48(4): 54-62. https://doi.org/10.11896/jsjkx.200800082
[9] 温馨, 闫心怡, 陈泽华.
基于等价关系的最小乐观概念格生成算法
Minimal Optimistic Concept Generation Algorithm Based on Equivalent Relations
计算机科学, 2021, 48(3): 163-167. https://doi.org/10.11896/jsjkx.200100046
[10] 江郑, 王俊丽, 曹芮浩, 闫春钢.
一种基于微服务架构的服务划分方法
Method of Service Decomposition Based on Microservice Architecture
计算机科学, 2021, 48(12): 17-23. https://doi.org/10.11896/jsjkx.210500078
[11] 刘栅杉, 朱海龙, 韩晓霞, 穆全起, 贺维.
基于主成分回归和分层置信规则库的企业风险评估模型
Enterprise Risk Assessment Model Based on Principal Component Regression and HierarchicalBelief Rule Base
计算机科学, 2021, 48(11A): 570-575. https://doi.org/10.11896/jsjkx.201200038
[12] 曾惠坤, 米据生, 李仲玲.
形式背景中概念及约简的动态更新方法
Dynamic Updating Method of Concepts and Reduction in Formal Context
计算机科学, 2021, 48(1): 131-135. https://doi.org/10.11896/jsjkx.200800018
[13] 李莉.
多赢家投票理论的研究进展
Survey on Multi-winner Voting Theory
计算机科学, 2021, 48(1): 217-225. https://doi.org/10.11896/jsjkx.200600013
[14] 游兰, 韩雪薇, 何正伟, 肖丝雨, 何渡, 潘筱萌.
基于改进Seq2Seq的短时AIS轨迹序列预测模型
Improved Sequence-to-Sequence Model for Short-term Vessel Trajectory Prediction Using AIS Data Streams
计算机科学, 2020, 47(9): 169-174. https://doi.org/10.11896/jsjkx.190800060
[15] 李雨蓉, 刘杰, 刘亚林, 龚春叶, 王勇.
面向语音分离的深层转导式非负矩阵分解并行算法
Parallel Algorithm of Deep Transductive Non-negative Matrix Factorization for Speech Separation
计算机科学, 2020, 47(8): 49-55. https://doi.org/10.11896/jsjkx.190900202
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!