摘要
汉语句模对计算机在处理自然语言时具有重要作用,可以使其更好地理解和分析汉语文本、抽取文本信息,提高自然语言处理的准确性和效率。但由于中文文本表达存在一定的灵活性和多样性,使得目前现有的句模存在匹配精度低、句模数量多、难以完全覆盖所有句子等问题,阻碍了句模在具体领域实现广泛应用和发展。针对以上的不足,文章提出基于句子层次结构的语义句模(HSST)。该句模以句子是嵌套的、有层次结构的,句子结构并非单向线性的为构建依据,使用多个句模且根据句子的层次结构对这些句模进行组合,大大减少了句模的数量,提高句模的匹配精度,并使得其对中文文本的覆盖面更广,使机器能更准确有效地理解与抽取文本语义信息。
Chinese sentence template plays an important role in natural language processing.It can make computer understand and analyze Chinese texts better,extract text information,and improve the accuracy and efficiency of natural language processing.However,due to the flexibility and diversity of Chinese texts expression,the existing sentence template have low matching accuracy,a large number of sentence template,and it is difficult to completely cover all sentences,which hinders the wide application and development of sentence template in specific fields.In view of the above shortcomings,this paper proposes a semantic sentence template named Hierarchical Structure-based Sentence Template(HSST).Based on the fact that sentences are nested and have hierarchical structure,and the sentence structure is not unidirectional linear,Hierarchical Structure-based Sentence Template uses multiple sentence template and combines these sentence template according to the hierarchical structure of the sentence,which greatly reduces the number of sentence template,improves the matching accuracy of sentence template,and makes it cover a wider range of Chinese texts,so that the machine can understand and extract the semantic information of the text more accurately and effectively.
作者
余小鹏
徐健儿
王振佩
姚小桐
YU Xiaopeng;XU Jianer;WANG Zhenpei;Yao Xiaotong(School of Management,Wuhan Institute of Technology,Wuhan 430205,China;School of Computer Science and Engineering,Wuhan Institute of Technology,Wuhan 430205,China)
出处
《长江信息通信》
2024年第1期132-134,共3页
Changjiang Information & Communications
基金
教育部人文社会科学研究规划基金项目(No.19YJA880077)。
关键词
句模
自然语言处理
信息抽取
层次结构
sentence Template
natural language processing
information extraction
hierarchical structure
