Please wait a minute...
New Technology of Library and Information Service  2012, Vol. 28 Issue (6): 29-35    DOI: 10.11925/infotech.1003-3513.2012.06.05
Current Issue | Archive | Adv Search |
The Research on Concept Retrieval Model Based on Rhombus-thinking Process
Yu Xiaoyi1, Liu Xu1, Qiu Jiangnan2, Dong Jinxia2
1. Dalian University of Technology Library, Dalian 116085, China;
2. School of Management Science and Engineering, Dalian University of Technology, Dalian 116024, China
Download: PDF(799 KB)   HTML  
Export: BibTeX | EndNote (RIS)      
Abstract  In this paper, the model of using rhombus-thinking method to solve retrieval problems is introduced into the Ontology-based concept retrieval model. This paper gives the algorithms of keywords’ matter element divergent expansion and extended words’ quantify convergence, and designs the experiment to prove that the model can improve concept retrieval recall rate and precision rate, and resolves the problem of synonym and polyseme in terms.At the same time, the Ontology-based retrieval recommended function is realized.
Key wordsConcept retrieval      Retrieval model      Rhombus-thinking method      Ontology     
Received: 18 April 2012      Published: 30 August 2012
: 

G250

 

Cite this article:

Yu Xiaoyi, Liu Xu, Qiu Jiangnan, Dong Jinxia. The Research on Concept Retrieval Model Based on Rhombus-thinking Process. New Technology of Library and Information Service, 2012, 28(6): 29-35.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2012.06.05     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2012/V28/I6/29

[1] 张辉,王英林. 基于本体的面向概念信息检索模型研究[J]. 微计算机信息 , 2009,25(2-3):185-187.(Zhang Hui,Wang Yinglin.Research of Ontology-based and Conceptual-orientend Information Retrieval Model[J]. Control & Automation, 2009,25(2-3):185-187.)

[2] 李蕾, 王楠, 钟义信,等. 基于语义网络的概念检索研究与实现[J]. 情报学报 , 2000,19(5):525-531.(Li Lei, Wang Nan,Zhong Yixin,et al.Research and Implementation of Concept Retrieval Based on the Semantic Network[J]. Journal of the China Society for Scientific and Technical Information,2000,19(5):525-531.)

[3] 张中夏,周兴社,王海鹏.基于本体与上下文感知矩阵的查询扩展算法[J]. 电子设计工程 ,2011,19(7):14-16.(Zhang Zhongxia,Zhou Xingshe,Wang Haipeng.A Query Expansion Algorithm Based on Ontology and Context-awareness Matrix[J].Electronic Design Engineering,2011,19(7):14-16.)

[4] 孙海霞,钱庆,成颖. 基于本体的语义相似度计算方法研究综述[J]. 现代图书情报技术 ,2010(1):51-56.(Sun Haixia,Qian Qing,Cheng Ying.Review of Ontology-based Semantic Similarity Measuring[J].New Technology of Library and Information Service, 2010(1):51-56.)

[5] 郗君甫,刘国华,唐军军,等. 基于本体的关系数据库关键词语义查询扩展方法[J]. 燕山大学学报 ,2010,34(3):232-236.(Xi Junfu,Liu Guohua,Tang Junjun,et al.A Semantic Expansion Method of Keywords Query Based on Ontology over Relational Database[J].Journal of Yanshan University, 2010,34(3):232-236.)

[6] 杜小勇,李曼,王珊. 本体学习研究综述[J]. 软件学报 ,2006,17(9):1837-1844.(Du Xiaoyong,Li Man,Wang Shan.A Survey on Ontology Learning Research[J].Journal of Software,2006,17(9):1837-1844.)

[7] 刘云峰. 基于潜在语义分析的中文概念检索研究[D].武汉:华中科技大学,2005.(Liu Yunfeng.Research of Chinese Concept Retrieval Based on Latent Semantic Analysis[D].Wuhan:Huazhong University of Science and Technology,2005.)

[8] 蔡文. 可拓学概述[J]. 系统工程理论与实践 , 1998,18(1):76-84.(Cai Wen.Extenics Overview [J]. Systems Engineering—Theory & Practice,1998,18(1):76-84.)

[9] 裘江南, 王磊, 王宁. 基于描述逻辑的概念检索模型[J]. 辽宁工程技术大学学报:自然科学版 , 2009,28(3):435-438.(Qiu Jiangnan,Wang Lei,Wang Ning.Concept Retrieval Model Based on Description Logic[J]. Journal of Liaoning Technical University:Natural Science Edition, 2009,28(3):435-438.)

[10] Wu Z B, Palmer M. Verb Semantics and Lexical Selection[C].In: Proceedings of the 32nd Annual Meeting of the Associations for Computational Linguistics.Stroudsburg, PA, USA:Association for Computational Linguistics,1994:133-138.

[11] Sussna M. Word Sense Disambiguation for Free-text Indexing Using a Massive Semantic Network[C].In: Proceedings of the 2nd International Conference on Information and Knowledge Managment.New York, NY, USA:ACM Press,1993:67-74.

[12] 吕刚,郑诚.改进的基于概念相似度的文本检索[J]. 计算机工程 ,2010,36(12):55-57.(Lv Gang,Zheng Cheng.Modified Text Retrieval Based on Concept Similarity[J]. Computer Engineering,2010,36(12):55-57.)

[13] 裘江南, 李丽冬, 吴力文. 客观知识体系中的相关性研究[J]. 情报学报 , 2009,28(3):362-367.(Qiu Jiangnan, Li Lidong, Wu Liwen.The Research on Relatedness in Objective Knowledge System[J]. Journal of the China Society for Scientific and Technical Information, 2009,28(3):362-367.)

[14] 秦健. 实用分类系统与语义网:发展现状和研究课题[J]. 现代图书情报技术 , 2004(1):16-23.(Qin Jian. Ontologies and Semantic Web:Current Development and Research Agenda[J]. New Technology of Library and Information Service, 2004(1):16-23.)

[15] Budanitsky A, Hirst G. Evaluating Wordnet-based Measures of Lexical Semantic Relatedness[J]. Computational Linguistics, 2006,32(1):13-47.
[1] Shiqi Deng,Liang Hong. Constructing Domain Ontology for Intelligent Applications: Case Study of Anti Tele-Fraud[J]. 数据分析与知识发现, 2019, 3(7): 73-84.
[2] Zhu Fu,Yuefen Wang,Xuhui Ding. Semantic Representation of Design Process Knowledge Reuse[J]. 数据分析与知识发现, 2019, 3(6): 21-29.
[3] Guangshang Gao. A Survey of User Profiles Methods[J]. 数据分析与知识发现, 2019, 3(3): 25-35.
[4] Ying Wang,Li Qian,Jing Xie,Zhijun Chang,Beibei Kong. Building Knowledge Graph with Sci-Tech Big Data[J]. 数据分析与知识发现, 2019, 3(1): 15-26.
[5] Youshi He,Shufang He. Sentiment Mining of Online Product Reviews Based on Domain Ontology[J]. 数据分析与知识发现, 2018, 2(8): 60-68.
[6] Huihui Tang,Hao Wang,Zixuan Zhang,Xueying Wang. Extracting Names of Historical Events Based on Chinese Character Tags[J]. 数据分析与知识发现, 2018, 2(7): 89-100.
[7] Beibei Pang,Juanqiong Gou,Wenxin Mu. Extracting Topics and Their Relationship from College Student Mentoring[J]. 数据分析与知识发现, 2018, 2(6): 92-101.
[8] Shengchun Ding,Menglu Liu,Zhu Fu. Unified Multidimensional Model Based on Knowledge Flow in Conceptual Design[J]. 数据分析与知识发现, 2018, 2(2): 11-19.
[9] Haili Tu,Xiaobo Tang. Building Product Recommendation Model Based on Tags[J]. 数据分析与知识发现, 2017, 1(9): 28-39.
[10] Erjing Chen,Enbo Jiang. Review of Studies on Text Similarity Measures[J]. 数据分析与知识发现, 2017, 1(6): 1-11.
[11] Rujiang Bai,Fuhai Leng,Junhua Liao. An Improved Cosine Text Similarity Computing Method Based on Semantic Chunk Feature[J]. 数据分析与知识发现, 2017, 1(6): 56-64.
[12] Dan Wu,Chang Liu,Yi Li. Changing Sentiments of Pedestrian Navigation System Users[J]. 数据分析与知识发现, 2017, 1(5): 42-51.
[13] Mingxuan Huang. Cross Language Information Retrieval Model Based on Matrix-weighted Association Patterns Mining[J]. 数据分析与知识发现, 2017, 1(1): 26-36.
[14] Liu Jian,Bi Qiang,Liu Qingxu,Wang Fu. New Content Recommendation Service of Digital Literature[J]. 现代图书情报技术, 2016, 32(9): 70-77.
[15] Ding Heng,Lu Wei. Building Standard Literature Knowledge Service System[J]. 现代图书情报技术, 2016, 32(7-8): 120-128.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn