基于HNC理论的fk识别研究

HanFen Zang, Xiangfeng Wei, Quan Zhang
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引用次数: 0

摘要

全自动语义分析一直是自然语言处理的主要目标之一。为了达到这一目标,许多研究者在语义分析或标注方面付出了巨大的努力。在语法短语块识别和语义角色标注等浅层语义分析方面已经取得了一些不错的成果。本文介绍了层次概念网络(HNC)理论中的补充语义块(简称fK)。基于汉字的特征边界符号和概念,总结了计算机识别汉语句子中汉字的操作规则。在实验中识别fk时,这些规则非常有效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on the Recognition of fKs Based on HNC Theory
Full-automatic semantic analysis is at all times one of the main targets in natural language processing. Many researchers made great efforts in semantic analyzing or tagging to reach such target. There have been some good results in shallow semantic analysis such as recognizing syntax phrase chunks and labeling semantic roles. This paper introduces the supplementary semantic chunk (in short, fK) in the theory of Hierarchical Network of Concepts (HNC). Based on the characteristic boundary symbols and concepts of fKs, we sum up some operational rules for computer to recognize the fKs in Chinese sentences. These rules are quite effective when recognizing the fKs in an experiment.
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