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
- 文章访问数: 1475
- HTML全文浏览量: 142
- PDF下载量: 307
- 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

HTML全文

参考文献(29)

LIN D. An information-theoretic definition of similarity semantic distance in WordNet[C]. Proceedings of the 15th International Conference on Machine Learning, San Francisco, CA, USA, 1998: 296-304.

WU Z and PALMER M. Verbs semantics and lexical selection [C]. Proceedings of the 32nd Annual Meeting of the Association for Computational Linguistics, Stroudsburg, PA, USA, 1994: 133-138. doi: 10.3115/981732.981751.

RESNIK P. Semantic similarity in a taxonomy: an information based measure and its application to problems of ambiguity in natural language[J]. Journal of Artificial Intelligence Research, 1999, 11(7): 95-130. doi: 10.1613/jair. 514.

王桐, 王磊, 吴吉义, 等. WordNet中的综合概念语义相似度计算方法[J]. 北京邮电大学学报, 2013, 36(2): 98-101. doi: 10.13190/jbupt.201302.98.wangt.

WANG Tong, WANG Lei, WU Jiyi, et al. Semantic similarity calculation method of Comprehensive concept in WordNet[J]. Journal of Beijing University of Posts and Telecommunications, 2013, 36(2): 98-101. doi: 10.13190/ jbupt.201302.98.wangt.

WANG Junhua, ZUO Wanli, and PENG Tao. Hyponymy graph model for word semantic similarity measurement[J]. Chinese Journal of Electronics, 2015, 24(1): 96-101. doi: 10.1049/cje.2015.01.016.

刘群, 李素建. 基于《知网》的词汇语义相似度计算[C]. 第三届汉语词汇语义学研讨会论文集, 台北, 中国, 2002: 59-76.

LIU Qun and LI Sujian. Words semantic similarity computation based on HowNet[C]. Proceedings of the 3rd Chinese Lexical Semantics Workshop, Taipei, China, 2002: 59-76.

李国佳. 基于知网的中文词语相似度计算[J]. 智能计算机与应用, 2015, 5(3): 49-52. doi: 10.3969/j.issn.2095-2163.2015. 03.015.

LI Guojia. Chinese words similarity computation based on HowNet[J]. Intelligent Computer and Applications, 2015, 5(3): 49-52. doi: 10.3969/j.issn.2095-2163.2015.03.015.

张沪寅, 刘道波, 温春艳. 基于《知网》的词语语义相似度改进算法研究[J]. 计算机工程, 2015, 41(2): 151-156. doi: 10.3969/j.issn.1000-3428.2015.02.029.

ZHANG Huyin, LIU Daobo, and WEN Chunyan. Research on improved algorithm of word semantic similarity based on HowNet[J]. Computer Engineering, 2015, 41(2): 151-156. doi: 10.3969/j.issn.1000-3428.2015.02.029.

孙晶, 张东站. 基于逆概念频率的词语相似度计算[J]. 厦门大学学报(自然科学版), 2015, 54(2): 257-262. doi: 10.6043/ j.issn.0438-0479.2015.02.018.

SUN Jing and ZHANG Dongzhan. Word similarity computing based on inverse concept frequencies[J]. Journal of Xiamen University (Natural Science), 2015, 54(2): 257-262. doi: 10.6043/j.issn.0438-0479.2015.02.018.

BROWN P, PIETRA S, PIETRA V, et al. Word sense disambiguation using statistical methods[C]. Proceedings of the 29th Annual Meeting of the Association for Computational Linguistics, Berkeley, CA, USA, 1991: 264-270. doi: 10.3115/981344.981378.

关毅, 王晓龙. 基于统计的汉语词汇间语义相似度计算[C]. 第七届全国计算语言学联合学术会议论文集, 哈尔滨, 中国, 2003: 221-227.

GUAN Yi and WANG Xiaolong. A statistical measure of semantic similarity between Chinese words[C]. Proceedings of the 7th Joint Symposium on Computational Linguistics, Harbin, China, 2003: 221-227.

王石, 曹存根, 裴亚军, 等. 一种基于搭配的中文词汇语义相似度计算方法[J]. 中文信息学报, 2013, 27(1): 7-14. doi: 10.3969/j.issn.1003-0077.2013.01.002.

WANG Shi, CAO Cungen, PEI Yajun, et al. A collocation based method for semantic similarity measure for Chinese words[J]. Journal of Chinese Information Processing, 2013, 27(1): 7-14. doi: 10.3969/j.issn.1003-0077.2013.01.002.

李慧. 词语相似度算法研究综述[J]. 现代情报, 2015, 35(4):[13] 172-177. doi: 10.3969/j.issn.1008-0821.2015.04.035.

LI Hui. A review on the research of word similarity algorithms[J]. Journal of Modern Information, 2015, 35(4): 172-177. doi: 10.3969/j.issn.1008-0821.2015.04.035.

黄曾阳. HNC理论全书(第五册)[M]. 北京: 科学出版社, 2015: 1-102.

HUANG Zengyang. The Complete Book of Hierarchical Network of Concepts Theory (Book 5)[M]. Beijing: Science Press, 2015: 1-102.

苗传江. HNC(概念层次网络)理论导论[M]. 北京: 清华大学出版社, 2005: 1-49.

MIAO Chuanjiang. Introduction to HNC Theory[M]. Beijing: Tsinghua University Press, 2005: 1-49.

吴佐衍, 王宇. 基于HNC理论的词语相似度计算[J]. 中文信息学报, 2014, 28(2): 37-43. doi: 10.3969/j.issn.1003-0077. 2014.02.005.

WU Zuoyan and WANG Yu. A new measure of semantic similarity based on hierarchical network of concepts[J]. Journal of Chinese Information Processing, 2014, 28(2): 37-43. doi: 10.3969/j.issn.1003-0077.2014.02.005.

史燕. 基于HNC的汉语句子相似度算法的研究[D]. [硕士论文], 江苏大学, 2009: 14-19. doi: 10.7666/d.y1604350.

SHI Yan. The research on Chinese sentence similarity algorithm based on HNC[D]. [Master dissertation], Jiangsu University, 2009: 14-19. doi: 10.7666/d.y1604350.

施引文献

资源附件(0)

访问统计