计算机科学 ›› 2010, Vol. 37 ›› Issue (5): 197-202.

• 人工智能 • 上一篇    下一篇

一种基于修饰关系的自然语言语义分析方法

田卫新,朱福喜,但志平   

  1. (武汉大学计算机学院 武汉430072);(三峡大学电气信息学院 宜昌443000)
  • 出版日期:2018-12-01 发布日期:2018-12-01

New Approach to Analyzing Meaning of Natural Language on Modi行ing Relations

TIAN Wei-xin,ZHU Fu-xi,DAN Zhi-ping   

  • Online:2018-12-01 Published:2018-12-01

摘要: 自然语言语义分析是自然语言处理技术走向深层应用的瓶颈。当前在概念、关系层次上的语义分析方法主要有两种:基于统计的特征向量抽取方法和基于语义词典(WordNct, HowNct等)的语义相似度计算方法。对于具体应用这两种方法都具有较大不足,前者由于统计模型的关系只适用于段落、篇章或多文档等粗粒度的语义分析,而不适合在句子词汇一级的应用;后者能方便处理实体概念之间的各种关系,但是如果想正确处理真实文本中的复杂修饰关系如概念与事件、概念与概念修饰、事件与事件修饰等关系,还需对语义词典和计算方法做进一步的扩展。提出了按照真实文本语句中词语之间修饰关系建立知识库,并设计了根据该知识库中已有修饰关系计算未知关系的算法;提出了可以依照修饰关系建立自然语言构句法的思路并给出了相关算法;最后给出了在语义分析系统上的实验,结果证明该方法是有效的。

关键词: 自然语言处理,语义分析,修饰关系,知识库

Abstract: Acquiring the meaning of natural language is a bottleneck to make deeper use of natural language processing (NLP). There are two main measures on analyzing meaning of natural language at conception-relation level: one is the method of extracting characteristic vectors based on statistics, and the other one is method of computing semantic similarities according to semantic dictionary like WordNet or HowNet. Both of the two methods have weakness when putting them to applications. The previous is only applicable to analyze the meaning of those materials with big granularitics such as paragraphs, documents or multi-documents, but is not fit for the applications at the level of sentences or words. The latter can deal all sorts of relations between conceptions easily, but when coming to complicated modified relations between conceptions and events, conceptions and conceptions or events and events, the semantic dictionary and computing method shall be extended. This paper presented a new method to structure semantic knowledge base(SKB) according to the modifying relation of real context; algorithm of computing unknown relations on the knowledge base was presented; we pointed out the way to design the rules of constructing natural language sentences under modifying relation and present the algorithm; in the end we made experiment on the platform developed in the light of the theory mentioned above and the result shows the theory is feasible.

Key words: NLP, Syntax, Semantic, Modifying relations, Knowledge base

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