基于概念基元的词语相似度计算研究

池哲洁; 张全

doi:10.11999/JEIT160176

基于概念基元的词语相似度计算研究

doi: 10.11999/JEIT160176

池哲洁^1, ,,
张全¹

基金项目:

国家863计划十二五项目(2012AA011102)，国家语委十二五科研项目(YB125-53)

计量
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- 被引次数: 0
出版历程
- 收稿日期: 2016-02-25
- 修回日期: 2016-09-14
- 刊出日期: 2017-01-19

Word Similarity Measurement Based on Concept Primitive

CHI Zhejie^{1
, ,},
ZHANG Quan¹

Funds:

The Twelfth Five-Year Project of National 863 Program of China (2012AA011102), The State Language Commission Twelfth Five-Year Research Project (YB125-53)

摘要

摘要: 词语相似度的计算在机器翻译、信息检索等多个领域有重要作用。该文以概念层次网络理论的概念基元符号系统为语义资源，在共性与差异性对比思想下，提出一个涵盖层次性、网络性、对比对偶特性、挂靠特性及五元组信息的多维度词语相似度计算方法；在节点深度和节点距离度量上，引入权重以增加不同层次间的区分程度。在人工打分的测试集上进行实验，结果表明该方法计算的相似度与人工判断的符合程度较好，兼容度、相关系数和序对符合度分别达到0.812, 0.786和0.775；同时，相关性检验的结果也显示该方法的计算值与人工打分显著相关。
- 词语相似度 /
- 语义距离 /
- 概念层次网络 /
- 概念基元
Abstract: Word similarity measurement plays an important role in machine learning, information retrieval and many other fields. Regarding the concept primitive symbol system of Hierarchical network of concepts theory as semantic resource and comparing commonness with difference, a multi-dimensional computational method for similarity is proposed which considers the hierarchy, netted nature, comparability and duality, attached feature and quintuple information of the system. Weight strategy is introduced for node depth and distance measurement to increase the discrimination of node level. Experiment on manual scoring test set shows that the computed similarities are consistent with human judgments. The proposed method achieves 0.812, 0.786, and 0.775 in compatibility degree, correlation coefficient, and ordinal pair conformity respectively. Meanwhile, the result of correlation test further proofs that the computed similarities and humans scores are significantly correlated.
- Word similarity /
- Semantic distance /
- Hierarchical network of concepts /
- Concept primitive

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参考文献(29)

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