Please wait a minute...
Advanced Search
现代图书情报技术  2012, Vol. 28 Issue (1): 19-26     https://doi.org/10.11925/infotech.1003-3513.2012.01.04
  数字图书馆 本期目录 | 过刊浏览 | 高级检索 |
领域本体学习方法和技术研究综述
刘萍, 胡月红
武汉大学信息资源研究中心 武汉 430072
Review on Ontology Learning Methods and Techniques
Liu Ping, Hu Yuehong
Center for Studies of Information Resources, Wuhan University, Wuhan 430072, China
全文: PDF (500 KB)   HTML  
输出: BibTeX | EndNote (RIS)      
摘要 分析本体学习的内容,对本体学习的发展进行评述;对领域本体学习过程中的几个关键任务——领域概念抽取、概念关系的识别进行深入的分析;总结领域本体学习的发展趋势。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
刘萍
胡月红
关键词 领域本体本体学习学习技术    
Abstract:This paper describes the elements of Ontology learning and the development of learning methods. The key tasks of Ontology learning, including concept extraction and relationship identification are analyzed in detail. Finally, it summarizes the challenges and developing trend in Ontology learning.
Key wordsDomain    Ontology    Ontology learning    Learning techniques
收稿日期: 2011-09-08      出版日期: 2012-02-26
: 

TP182

 
基金资助:

本文系教育部人文社会科学青年基金项目“高校专家知识地图构建研究”(项目编号:10YJC870022)的研究成果之一。

引用本文:   
刘萍, 胡月红. 领域本体学习方法和技术研究综述[J]. 现代图书情报技术, 2012, 28(1): 19-26.
Liu Ping, Hu Yuehong. Review on Ontology Learning Methods and Techniques. New Technology of Library and Information Service, 2012, 28(1): 19-26.
链接本文:  
https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/10.11925/infotech.1003-3513.2012.01.04      或      https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/Y2012/V28/I1/19
[1] Borst W N. Construction of Engineering Ontologies for Knowledge Sharing and Reuse[D]. Enschede: University of Twente, 1997.

[2] 邓志鸿,唐世渭,张铭,等. Ontology研究综述[J]. 北京大学学报:自然科学版 , 2002, 38(5):730-738.

[3] Gómez P A, Manzano M D. A Survey of Ontology Learning Methods and Techniques[EB/OL]. [2011-09-23]. http://www.sti-innsbruck.at/fileadmin/documents/deliverables/Ontoweb/ D1.5.pdf

[4] Maedche A, Staab S. Ontology Learning for the Semantic Web[C]. In: Proceedings of the IEEE Intelligent Systems. 2001.

[5] Shamsfard M, Barforoush A. Learning Ontologies from Natural Language Texts[J]. International Journal of Human Computer Studies, 2004,60(1): 17-63.

[6] 任柏青. 基于关系数据库的领域本体构建方法的研究与实践[D]. 北京:北京邮电大学,2009.

[7] 贾黎莉. Ontology构建中概念间关系的研究[D]. 北京:中国农业科学院,2007.

[8] Qin J, Paling S. Converting a Controlled Vocabulary into an Ontology: The Case of GEM[J/OL]. Information Research, 2001, 6(2). [2011-09-23]. http://informationr.net/ir/6-2/paper94.html.

[9] Dagobert S. Building a Rich Ontology from AGROVOC[OL]. [2011-10-13]. http://www.dsoergel.com/cv/ B93.ppt.

[10] Jannink J. Thesaurus Entry Extraction from an On-line Dictionary[C]. In: Proceedings of the 2nd International Conference on Information Fusion, Sunnyvale, CA,USA. 1999:599-607.

[11] Rigau G. Automatic Acquisition of Lexical Knowledge from MRDs[D]. Barcelona: Universitat Politècnica de Catalunya, 1998.

[12] Suryanto H, Compton P. Discovery of Ontologies from Knowledge Bases[C]. In: Proceedings of the 1st International Conference on Knowledge Capture, British Columbia,Canada. 2001:171-178.

[13] Johannesson P. A Method for Transforming Relational Schemas into Conceptual Schemas[C].In: Proceedings of the 10th International Conference on Data Engineering.Boston:IEEE Computer Society,1994:190-201.

[14] Stojanovic L, Stojanovic N, Volz R. Migrating Data-intensive Websites into the Semantic Web[C]. In: Proceedings of the 17th ACM Symposium on Applied Computing. New York: ACM Press, 2002:1100-1107.

[15] Deitel A, Faron C, Dieng R. Learning Ontologies from RDF Annotations[C]. In: Proceedings of the IJCAI Workshop in Ontology Learning, Seattle, USA. 2001.

[16] Papatheodorou C, Vassiliou A, Simon B. Diseovery of Ontologies for Learning Resources Using Word-based Clustering[C]. In: Proceedings of the World Conference on Educational Multimedia, Hypermedia and Telecommunications. Chesa Peake: AACE, 2002:1523-1528.

[17] Modica G, Gal A, Jamil H M. The Use of Machine-Generated Ontologies in Dynamic Information Seeking[C]. In: Proceedings of the 9th International Conference on Cooperative Information Systems. Springer-Verlag, 2001.

[18] Volz R, Oberle D, Staab S, et al. OntoLiFT Prototype[EB/OL]. [2011-10-13]. http://wonderweb.man. ac.uk/deliverables/documents/D11.pdf

[19] Wagner A. Enriching a Lexical Semantic Net with Selectional Preferences by Means of Statistical Corpus Analysis[C]. In: Proceedings of the 1st Workshop on Ontology Learning, Berlin, Germany. 2000.

[20] Chalendar G D, Grau B. SVETLAN: A System to Classify Nouns in Context[C]. In: Proceedings of the 1st Workshop on Ontology Learning, Berlin, Germany. 2000.

[21] Bisson G, Nédellec C, Caamero D. Designing Clustering Methods for Ontology Building-The Mo'K Workbench [C]. In: Proceedings of the ECAI Ontology Learning Workshop, Berlin, Germany. 2000.

[22] Cimiano P, Stumme G, Hotho A. Conceptual Knowledge Processing with Formal Concept Analysis and Ontologies[C]. In: Proceedings of the 2nd International Conference on Formal Concept Analysis (ICFCA). Springer, 2004:189-207.

[23] Faure D, Nédellec C. Knowledge Acquisition of Predicate Argument Structures from Technical Texts Using Machine Learning: The System ASIUM[C]. In: Proceedings of the 11th European Workshop (EKAW'99). Springer-Verlag, 1999:329-334.

[24] Maedche A, Volz R. The Text-To-Onto Ontology Extraction and Maintenance Environment[C]. In: Proceedings of the ICDM Workshop on Integrating Data Mining and Knowledge Management, San Jose, California, USA. 2001.

[25] Velardi P, Navigli R, Missikoff M. Integrated Approach for Web Ontology Learning and Engineering[C]. In: Proceedings of the IEEE Computer. 2002:60-63.

[26] Sabou M. From Software APIs to Web Service Ontologies: A Semi-Automatic Extraction Method[C]. In: Proceedings of International Semantic Web Conference (ISWC), Hiroshima, Japan. 2004.

[27] Bourigault D. Surface Grarnmatieal Analysis for the Extraction of Terminological Noun Phrase[C]. In: Proceedings of International Conference on Computational Linguistics (COLING). 1992:977-981.

[28] Sabou M, Chris W. Learning Domain Ontologies for Web Service Descriptions: An Experiment in Bioinformatics[C]. In: Proceedings of the 14th International Conference on World Wide Web. New York, USA: ACM, 2005.

[29] Shamsfard M, Barforoush A. Learning Ontologies from Natural Language Texts[J]. International Journal of Human-Computer Studies, 2004,60(1):17-63.

[30] 郑家恒,卢娇丽.关键词抽取方法的研究[J]. 计算机工程 , 2005, 31(18):194-196.

[31] 翟林.领域本体的半自动构建方法研究与实现[D]. 南京:东南大学, 2005.

[32] 黄婵. 领域本体的构建及其在Web信息抽取中的应用研究[D]. 赣州:江西理工大学, 2009.

[33] Navigli R, Velardi P, Gangemi A. Ontology Learning and Its Application to Automated Terminology Translation[J]. IEEE Intelligent Systems, 2003,18(1):22-31.

[34] 于娟. 基于文本的领域本体学习方法及其应用研究[D].大连:大连理工大学,2010.

[35] 奉国和,郑伟. 文本分类特征降维研究综述[J]. 图书情报工作 ,2011,55(9):1001-1008.

[36] Chien L F. PAT-Tree-Based Adaptive Key-phrase Extraction for Intelligent Chinese Information Retrieval[J]. Information Processing & Management, 1999, 35(4):501-521.

[37] 陈文亮,朱靖波,姚天顺,等.基于Bootstrapping的领域词汇自动获取[C]. In: Proceedings of the JSCL. 北京:清华大学, 2003:67-72.

[38] Ji D H, Zhao S J, Xiao G Z. Chinese Document Re-ranking Based on Automatically Acquired Term Resource[J]. Language Resource & Evaluation, 2009, 43(4):385-406.

[39] 张敏,耿焕同,王煦法.一种利用BC方法的关键词自动提取算法研究[J]. 小型微型计算机系统 , 2007,28 (1):189-192

[40] 魏瑞斌. 社会网络分析在关键词网络分析中的实证研究[J]. 情报杂志 ,2009,28(9):46-49.

[41] 何琳. 领域本体的半自动构建及检索研究[M]. 南京:东南大学出版社, 2009.

[42] 周浪.中文术语抽取若干问题研究[D]. 南京:南京理工大学,2009.

[43] Wu S H, Hsu W L. SOAT: A Semi-automatic Domain Ontology Acquisition Tool from Chinese Coprus[C]. In: Proceedings of 19th International Conference on Computational Linguistics (COLING), Taipei, Taiwan.2002.

[44] 翟笃风,刘柏嵩.政务领域本体术语的自动抽取[J]. 现代图书情报技术 , 2010(4):59-65.

[45] Frantzi K T, Ananiadou S. The C-value/NC-Value Domain-independent Method for Multiword Term Extraction[J]. Journal of Natural Language Processing, 1999,6(3):145-179.

[46] 王世清.本体构建中建立概念间关系方法研究[D]. 北京:中国农业科学院,2010.

[47] Brewster C, Simon J, Lueiano J, et al. Issues in Learning an Ontology from Text[C]. In: Proceedings of the Bio-Ontologies Special Interest Group Workshop 2008: Knowledge in Biology. 2008.

[48] Hearst M A. Automatic Acquisition of Hyponyms from Large Text Corpora[C]. In: Proceedings of the 14th Conference on Computational Linguistics. 1992:539-545.

[49] Hearst M A. Automated Discovery of WordNet Relations[A].//Fellbaum C. WordNet: An Electronic Lexical Database and Some of Its Applications[M]. MIT Press, 1998.

[50] Agiehtein E,Eskin E, Gravano L. Combining Strategies for Extracting Relations from Text Collections[C]. In: Proceedings of the ACM SIGMOD Workshop on Data Mining and Knowledge Diseovery.2000: 86-95.

[51] Ahlnad K, Tariq M, Vrusias B, et al. Corpus-based Thesaurus Construction for Image Retrieval in Speeialist Domains[C] In: Proceedings of the 25th European Conference on Advances in Information Retrieval(ECIR), Pisa, Italy. 2003: 502-510.

[52] Pantel P, Ravichandran D, Hovy E. Towards Terascale Knowledge Acquisition[C]. In: Proceedings of the 20th International Conference on Computational Linguisties(COLING), Geneva, Switzerland.2004.

[53] Nedellec C. Corpus-based Learning of Semantic Relations by the ILP System Asium[C]. In: Proceedings of Learning Languagein Logic, Berlin,Germany.2000:259-278.

[54] Kavalec M, Maedche A, Svateck V. Discovery of Lexical Entries for Non-taxonomic Relations in Ontology Learning[C]. In:Proceedings of Conference on Current Trends in Theory and Practice of Informatics (SOFSEM). 2004:249-256.

[55] Harris Z S. Mathematical Structures of Language[M]. New York: Wiley Inter-Science, 1968.

[56] 傅魁.基于Web的本体学习研究[D]. 武汉:武汉理工大学,2007.

[57] Zhou L. Ontology Learning: State of the Art and Open Issues[J]. Information Technology Management, 2007,8(3):241-252.

[58] Faure D, Nedellec C. A Corpus-based Conceptual Clustering Method for Verb Frames and Ontology Acquisition [C]. In: Proceedings of the LREC Workshop on Adapting Lexical and Corpus Resources to Sublanguages and Applications. Granada: LREC, 1998:5-12.

[59] 王磊,周宽久,仇鹏. 领域本体自动构建研究[J]. 情报学报 , 2010, 29(1):45-52.

[60] Zhang G Q, Troy A D, Bourgoin K. Bootstrapping Ontology Learning for Information Retrieval Using Formal Concept Analysis and Information Anchors[C]. In: Proceedings of the 14th International Conference on Conceptual Structures, Alborg.2006.

[61] Obitko M, Snáel V, Smid J. Ontology Design with Formal Concept Analysis[C]. In: Proceedings of the CLA 2004 International Workshop on Concept Lattices and Their Applications. 2004: 111-119.

[62] 张云中.基于形式概念分析的领域本体构建方法研究[D].长春:吉林大学, 2009.

[63] Han J, Kamber M. Data Mining: Concepts and Techniques[R/OL]. [2011-01-23]. http://134.208.3.165/ course/2006/Fall/Data_mining/06.pdf.

[64] Maedche A, Staab S. Discovering Conceptual Relations from Text[C]. In: Proceedings of the European Conference on Artificial Intelligence (ECAI). 2000: 321-325.

[65] Maedche A, Staab S. Ontology Learning for the Semantic Web[C]. In: Proceedings of the IEEE Intelligent Systems. 2001: 72-79.

[66] 王俊华. 基于文本的半监督领域领域本体构建[D]. 长春:吉林大学,2010.

[67] Sanderson M,Croft B. Deriving Concept Hierarchies from Text[C]. In: Proceedings of the Special Interest Group on Information Retrieval (SIGIR). 1999:206-213.

[68] 杨芬.本体学习中概念和关系抽取方法研究[D]. 重庆:重庆大学,2010.

[69] 刘柏崇. 基于Web的通用本体学习方法[D]. 杭州:浙江大学,2007.

[70] Strube M, Ponzetto S P. WikiRelate! Computing Semantic Relatedness Using Wikipedia[C]. In: Proceedings of the 21st National Conference on Artificial Intelligence. 2006.

[71] Gabrilovich E, Markovich S. Computing Semantic Relatedness Using Wikipedia-based Explicit Semantic Analysis[C]. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI'07), Hyderabad, India. 2007.
[1] 何有世, 何述芳. 基于领域本体的产品网络口碑信息多层次细粒度情感挖掘*[J]. 数据分析与知识发现, 2018, 2(8): 60-68.
[2] 唐慧慧, 王昊, 张紫玄, 王雪颖. 基于汉字标注的中文历史事件名抽取研究*[J]. 数据分析与知识发现, 2018, 2(7): 89-100.
[3] 陆佳莹,袁勤俭,黄奇,钱韵洁. 基于概念格理论的产品领域本体构建研究*[J]. 现代图书情报技术, 2016, 32(5): 38-46.
[4] 鲍玉来,毕强. 蒙古文音乐领域的语义检索初探*[J]. 现代图书情报技术, 2016, 32(11): 94-100.
[5] 朱惠,杨建林,王昊. 中文领域专业术语层次关系构建研究*[J]. 现代图书情报技术, 2016, 32(1): 73-80.
[6] 张帆, 乐小虬. 领域科技文献创新点句中主题属性实例识别方法研究[J]. 现代图书情报技术, 2015, 31(5): 15-23.
[7] 段宇锋, 朱雯晶, 陈巧, 刘伟, 刘凤红. 条件随机场与领域本体元素集相结合的未登录词识别研究[J]. 现代图书情报技术, 2015, 31(4): 41-49.
[8] 段宇锋, 黄思思. 基于BFO构建中文植物物种多样性领域本体的研究[J]. 现代图书情报技术, 2015, 31(12): 72-79.
[9] 颜时彦, 王胜清, 罗云川, 黄浩军. 云环境下基于FCA的领域本体协作构建模式初探[J]. 现代图书情报技术, 2014, 30(3): 49-56.
[10] 姚晓娜, 祝忠明, 王思丽. 面向地学领域的自动语义标注研究[J]. 现代图书情报技术, 2013, (4): 48-53.
[11] 许鑫, 郭金龙. 基于领域本体的专题库构建——以中华烹饪文化知识库为例[J]. 现代图书情报技术, 2013, (12): 2-9.
[12] 郭金龙, 洪韵佳, 许鑫. 中华烹饪文化领域本体构建及其应用[J]. 现代图书情报技术, 2013, (12): 10-18.
[13] 洪韵佳, 许鑫. 基于领域本体的知识库多层次文本聚类研究——以中华烹饪文化知识库为例[J]. 现代图书情报技术, 2013, (12): 19-26.
[14] 金碧漪, 郭金龙, 许鑫. 利用领域本体优化文档检索的研究——基于KIM平台的设计与实现[J]. 现代图书情报技术, 2013, (12): 27-33.
[15] 唐晓波, 肖璐. 融合关键词增补与领域本体的共词分析方法研究[J]. 现代图书情报技术, 2013, 29(11): 60-67.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 2015 《数据分析与知识发现》编辑部
地址:北京市海淀区中关村北四环西路33号 邮编:100190
电话/传真:(010)82626611-6626,82624938
E-mail:jishu@mail.las.ac.cn