基于词法分析和语义分析的本体集成研究
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摘要
本体是领域共享概念模型明确的形式化规范说明,使得计算机对知识能够共享、重用和互操作,它在语义Web、知识数据工程和语义物联网等领域有着广泛的应用。然而,表示相似(或相同)领域共享概念模型的大部分本体由不同背景的知识工程师使用其各自术语构造和维护,这种本体之间的异构性阻碍了应用系统对知识的共享、重用和互操作。本体集成则是解决本体异构问题的方法之一,它的主要目的是建立来自不同数据源的描述相似(或相同)领域的两个本体中实体之间的匹配,并通过这些被建立的匹配构建集成本体。本文对本体的词法分析、语义分析以及一致性集成本体的构造等本体集成研究中的关键问题进行了深入探讨,主要研究成果如下：
(一)基于实体标记分析本体的词法信息。该方法首先使用WordNet里特殊的词法关系,扩展单词的合适词义到一组词义,然后通过组合单词的多个词义及本体里的语义元素(比如(?)、(?)和(?))形式化的定义实体标记。单词合适词义的扩展表示本体里单词在目前上下文中可能的意思,克服了仅发现单词合适词义的缺点,这有助于发现潜在的匹配。通过实验数据的分析,实体标记公以降低系统3%的查准率为代价提高了系统37%的查全率。
(二)提出一种语义的循环过滤方法删除候选匹配中的冗余匹配。该方法首先制定过滤规则,然后提出过滤算法,最后形式化定义过滤的充分性条件,并证明该循环过程可终止。通过实验数据的分析,语义循环过滤过程提高了系统22%的F测度值。
(三)基于苗述逻辑中最小公有包含(the least common subsumer)和最明确概念(he most specific concept)的主要思想,形式化的定义实体描述的最近包含(the closest subsumer)。基于最近包含,可推理出一组有意义的补充匹配。这些匹配经常出现在标准匹配结果中,但较少出现在其它解决方案的匹配结果中。实验数据的分析表明最近包含的定义加强了系统的查准率和查全率
(四)扩展结构包含推理算法分析本体的语义信息。该方法首先剖析组成本体的各种构造器和公理,然后基于实体标记构建实体的范式,使木体里暗含的语义信息和词法信息能够容易读出,最后通过调节实体间被允许的差异程度及放大和缩小实体对应的集合,比较两个实体范式间的句法结构,推理出实体间的匹配。通过实验数据的分析,该语义信息的分析方法提高了系统的查准率和查全率。
(五)利用微子图形式化地定义本体集成问题,并提出构建集成本体的算法。该算法在不改变异构本体语义的前提下使得集成本体采用最多的匹配,所采用的匹配仅起到连接两个异构本体的作用,反映了不同异构本体实体图间的搭桥。论文也证明了该算法所构建的集成本体是一致的。
An ontology, as a formal explicit specification of a shared conceptualization, is utilized to share, reuse and interoperate knowledge between soft agents. Currently, it has been adopted widely in many applicaitons such as semantic web, knowledge and data engineering, and semantic IoT (Internet of Things). However, most of these ontologies in similar (or same) domains are constructed and maintained by different knowledge engineers who have various backgrounds and use different terminologies to describe concepts. The heterogeneity between different ontologies for representing similar (or same) domains blocks sharing, reusing and interoperability across ontologies in application systems. Ontology integration methods deal with this issue. Its main task is to establish correspondences between entities, each from heterogeneous ontologies respectively derived from different data sources which represent similar (or same) domains, and then construct an integration ontology with the established correspondences. This dissertation discusses some key issues in an ontology integration, which include lexical analysis, semantic analysis, the construction of a consistent integration ontology and so on.
The main contributions of this dissertation are listed as follows:
1. Analyzing lexical information based on an entity notion. Considering special lexical relations in WordNet, this dissertation extends the sense of each word to a set of senses. This helps to include the possible senses of the word in some existing context instead of only finding the suitable one and supports potential relations between entities. This dissertation also formally defines an entity notion combining syntaxes (such as(?),(?) and3) with senses of words. By analyzing evaluations, this method descreases the precision of the system by3%, but helps to increases the recall of the system by37%.
2. Proposing an iterative and semantic filtering process to remove redundant matching candidates. We firstly draw up rules for filtering; secondly present a filtering algorithm; finally formally define sufficiency conditions for filtering and prove that the process is terminable. By analyzing evaluations, this method enhances the accuracy of the system.
3. Formally defining the closest subsumer of an entity description by thinking the least common subsumer and the most specific concept in description logics. Based on the definition, we produce the supplementary correspondences based on the filtered matching candidates, which exist in standard alignments but seldom appear in the alignments of other solutions. By analyzing evaluations, the definition helps to improve the recall and precision of the system.
4. Extending structural subsumption reasoning algorithms to analyze semantic information. This dissertation firstly parses various constructors and axioms in an ontology to make the implied semantics and lexical information to be combined together and read-off easily by rephrasing entities into normal forms based on the representation of an entity notion; and then compare the syntactical structures of normal forms, by zooming in (out) the sets related to the entities and adjusting the allowable degree for discrepancy between entities, to infer corrrespondences. By analyzing evaluations, the method for analyzing semantic information increases the recall and precision of the system.
5. Formally defining an ontology integration based on micro-sub graphes and proposing algorithms for constructing an integration ontology. The algorithms donot break semantic structure in heterogeneous ontologies and promise that the integration ontology adopte the most correspondences. The correspondences only bridge the heterogeneous ontologies. We also prove the established integration ontology is consistent.
(一)基于实体标记分析本体的词法信息。该方法首先使用WordNet里特殊的词法关系,扩展单词的合适词义到一组词义,然后通过组合单词的多个词义及本体里的语义元素(比如(?)、(?)和(?))形式化的定义实体标记。单词合适词义的扩展表示本体里单词在目前上下文中可能的意思,克服了仅发现单词合适词义的缺点,这有助于发现潜在的匹配。通过实验数据的分析,实体标记公以降低系统3%的查准率为代价提高了系统37%的查全率。
(二)提出一种语义的循环过滤方法删除候选匹配中的冗余匹配。该方法首先制定过滤规则,然后提出过滤算法,最后形式化定义过滤的充分性条件,并证明该循环过程可终止。通过实验数据的分析,语义循环过滤过程提高了系统22%的F测度值。
(三)基于苗述逻辑中最小公有包含(the least common subsumer)和最明确概念(he most specific concept)的主要思想,形式化的定义实体描述的最近包含(the closest subsumer)。基于最近包含,可推理出一组有意义的补充匹配。这些匹配经常出现在标准匹配结果中,但较少出现在其它解决方案的匹配结果中。实验数据的分析表明最近包含的定义加强了系统的查准率和查全率
(四)扩展结构包含推理算法分析本体的语义信息。该方法首先剖析组成本体的各种构造器和公理,然后基于实体标记构建实体的范式,使木体里暗含的语义信息和词法信息能够容易读出,最后通过调节实体间被允许的差异程度及放大和缩小实体对应的集合,比较两个实体范式间的句法结构,推理出实体间的匹配。通过实验数据的分析,该语义信息的分析方法提高了系统的查准率和查全率。
(五)利用微子图形式化地定义本体集成问题,并提出构建集成本体的算法。该算法在不改变异构本体语义的前提下使得集成本体采用最多的匹配,所采用的匹配仅起到连接两个异构本体的作用,反映了不同异构本体实体图间的搭桥。论文也证明了该算法所构建的集成本体是一致的。
An ontology, as a formal explicit specification of a shared conceptualization, is utilized to share, reuse and interoperate knowledge between soft agents. Currently, it has been adopted widely in many applicaitons such as semantic web, knowledge and data engineering, and semantic IoT (Internet of Things). However, most of these ontologies in similar (or same) domains are constructed and maintained by different knowledge engineers who have various backgrounds and use different terminologies to describe concepts. The heterogeneity between different ontologies for representing similar (or same) domains blocks sharing, reusing and interoperability across ontologies in application systems. Ontology integration methods deal with this issue. Its main task is to establish correspondences between entities, each from heterogeneous ontologies respectively derived from different data sources which represent similar (or same) domains, and then construct an integration ontology with the established correspondences. This dissertation discusses some key issues in an ontology integration, which include lexical analysis, semantic analysis, the construction of a consistent integration ontology and so on.
The main contributions of this dissertation are listed as follows:
1. Analyzing lexical information based on an entity notion. Considering special lexical relations in WordNet, this dissertation extends the sense of each word to a set of senses. This helps to include the possible senses of the word in some existing context instead of only finding the suitable one and supports potential relations between entities. This dissertation also formally defines an entity notion combining syntaxes (such as(?),(?) and3) with senses of words. By analyzing evaluations, this method descreases the precision of the system by3%, but helps to increases the recall of the system by37%.
2. Proposing an iterative and semantic filtering process to remove redundant matching candidates. We firstly draw up rules for filtering; secondly present a filtering algorithm; finally formally define sufficiency conditions for filtering and prove that the process is terminable. By analyzing evaluations, this method enhances the accuracy of the system.
3. Formally defining the closest subsumer of an entity description by thinking the least common subsumer and the most specific concept in description logics. Based on the definition, we produce the supplementary correspondences based on the filtered matching candidates, which exist in standard alignments but seldom appear in the alignments of other solutions. By analyzing evaluations, the definition helps to improve the recall and precision of the system.
4. Extending structural subsumption reasoning algorithms to analyze semantic information. This dissertation firstly parses various constructors and axioms in an ontology to make the implied semantics and lexical information to be combined together and read-off easily by rephrasing entities into normal forms based on the representation of an entity notion; and then compare the syntactical structures of normal forms, by zooming in (out) the sets related to the entities and adjusting the allowable degree for discrepancy between entities, to infer corrrespondences. By analyzing evaluations, the method for analyzing semantic information increases the recall and precision of the system.
5. Formally defining an ontology integration based on micro-sub graphes and proposing algorithms for constructing an integration ontology. The algorithms donot break semantic structure in heterogeneous ontologies and promise that the integration ontology adopte the most correspondences. The correspondences only bridge the heterogeneous ontologies. We also prove the established integration ontology is consistent.
引文
[I]R. Baeze-Yates and B. Ribeiro-Neto. Modern Information Retrieval [B]. Addison Wesley,1999, ch2:104-108.
[2]W. Nico Borst. Construction of Engineering Ontologies for Knowledge Sharing and Reuse[D]. PhD dissertation, Enschede:University of Twente,1997, chl:10-12.
[3]T. Berners-Lee, J. Hendler and O. Lassila. The semantic web[J]. Scientific American,2001, 284(05):34-43.
[4]World Wide Web Consortium (W3C)[EB/OL]. Available:http://www.w3.org/.
[5]Semantic Web[EB/OL]. Available:http://en.wikipedia.org/wiki/Semantic_web.
[6]Ontology (information science)[EB/OL]. Available: http://en.wikipedia.org/wiki/Ontology_information_science.
[7]T. Berners-Lee and J. Hendler. Publishing on the semantic web-the coming Internet revolution will profoundly affect scientific information[J]. Nature,2001,410(6832):1023-1024.
[8]D. Beneventano, S. Bergamaschi, F. Guerra and M. Vincini. Themomis approach to information integration[C].3rd International Conference on Enterprise Information Systems, Portugal,2001, 1082-1086.
[9]S. Bergamaschi, S. Castano and M. Vincini. Semantic integration of semi-structured and structured data sources[C]. SIGMOD Record, Enschede,1999,54-59.
[10]S. Bergamaschi, F. Guerra and M. Vincini. A data integration framework for e-commerce product classification[C].1st semantic web conference, London,2002,379-393.
[11]S. Albagli, R. Ben-Eliyahu-Zohary and S. E. Shimony. Markov network based ontology matching[J]. Journal of Computer and System Sciences, In Press, Accepted Manuscript,2012.
[12]M. Obitko, Translation between Ontologies in Multi-Agent Systems[EB/OL]. Available:http://keg.vse.cz/_slides/obitko-2007.pdf
[13]Xiaomeng Su. Sematnic Enrichment for ontology mapping[D]. Ph.D. dissertation, Dept. Electron.Eng., Norwegian Univ. of Seience and Technology,2004, ch3:40-45.
[14]郑晓庆.语义万维网的不确定知识表示与信任计算[D].浙江大学博士学位论文,2007,ch2：20-14.
[15]周丽平.DL-Lite本体的不一致处理方法研究[D].北京交通大学博士学位论文,201,ch3：30-35.
[16]徐凯丰.中文语义万维网本体匹配[D].上海交通大学博士学位论文,2010,ch2：19-25.
[17]汪鹏.本体映射关键问题研究[D].东南大学博士学位论文,2008,ch3：28-34.
[18]W. Nico Borst. Construction of Engineering Ontologies for Knowledge Sharing and ReusefD]. Ph.D. dissertation, Enschede University of Twente,1997, ch2:22-28.
[19]R. Studer, R. Benjamins and D. Fensel. Knowledge Engineering:Principles and Methods[J]. Data and Knowledge Engineeing,1998,25(122):161-197.
[20]I. Horrocks, P. F. Patel-Schneider and F. V. Harmelen. From shiq and rdf to owl:The making of a web ontology language[J]. Journal of Web Semantics,2003,17(01):19-29.
[21]F. Baader, D. Calvanese, et al. The Description Logic Handbook:Theory, Implementation and Applications[B]. Cambridge University Press,2003, ch2:46-99.
[22]K. Shafa'amri and J. Atoum. A Framework for Improving the Performance of Ontology Matching Techniques in Semantic Web[J]. International Journal of Advanced Computer Science and Application,2012,03(01):10-21.
[23]M. PREECE and A,GRAY P. Implementing a semanticWeb blackboard system using Jena[EB/OL]. Available:http://eprints.aktors.org/569/01/ImplSWBbUsingJena juc2006.pdf.
[24]X. Su and L. Ilebrekke. A comparative study of ontology languages and tools[C].7th IFIP-WG8.1 International Workshop on Evaluating of Modeling Methods in Systems Analysis and Design, Pairs,2002,1120-1126.
[25]X. Su and L. Ilebrekke. Using a semiotic framework for a comparative study of ontology languages and tools[J]. Information Modeling Methods and Methodologies,2004, 15(08):1102-1120.
[26]S. Luke and J. Heflin. Shoe, the proposed specification, shoe project[EB/OL]. Available:http://www.cs.umd.edu/projects/plus/SHOE/spec.html,2000.
[27]J. Heflin, J. Hendler, and S. Luke. Coping with changing ontologies in a distributed environment[C]. AAAI workshop on ontology management, San Francisco,1999,402-410.
[28]D. Fensel, M. Crubezy, et al. Oil &upml:A unifying framework for the knowledge web[C]. ECAI, Berlin, Germany,2000,1087-1098.
[29]M. Kolli and Z. Boufaida. A description logics formalization for the ontology matching[J]. Procedia Computer Science,2011,3(01):29-35.
[30]O. Lassila and R. Swick. Resource description framework (rdf) model and syntax specification [S]. w3c recommendation,1999.
[31]D. Brickley and R. Guha. Resource description framework schema specification 1.0[S]. w3c recommendation,2000.
[32]T. Bray, J. Paoli, et al. Extensible markup language (xml) 1.0 (second edition)[S]. w3c recommendation,2000.
[33]I. Horrocks, P. F. Patel-Schneider and F. van Harmelen. Reviewing the design of daml+oil:An ontology language for the semantic web[C]. AAAI, Mecigo,2002,792-797.
[34]I. Horrocks, F. van Harmelen and P. F. Patel-Schneider. Reference description of the daml+oil ontology markup language[EB/OL]. Available:http://www.daml.org/2001/03/reference.html.
[35]M. Kifer, G. Lausen and J. Wu. Logical foundations of object oriented and frame-based languages[J]. Journal of Computer Technologies,1995,12(05):185-200.
[36]D. McGuinness and F. van Harmelen eds. Owl web ontology language overview[S]. w3c proposed recommendation,2003.
[37]F. Harmelen, J. Hendler, et al. OWL Web Ontology Language Reference[EB/OL]. Available:http://www.w3.org/TR/2004/REC-owl-ref-20040210.2004.
[38]卢刘明,朱国进,陈家训.语义Web中几种语义描述语言的分析比较[J].计算机工程,2005,20(03)：1086-1092.
[39]胡鹤,刘大有,王生生.Web本体语言的分析与比较[J].计算机工程,2005,12(04)：870-876.
[40]R. MacGregor. Using a description classifier to enhance deductive inference[C].7th IEEE Conference on AI Application, Florida,1991,93-97.
[41]R. S. Cost, T. Finin, et al. ITTalks:A Case Study in the Semantic Web and DAML[EB/OL]. Available:http://www.semanticweb.org/SWWS/program/full/paper41.pdf
[42]T. Finin, W. Krueger, et al. Automatically Generated DAML Markup for Semistructured Documents[C]. AAAI Spring Symposium on Agent-Mediated Knowledge Management, Manchester,2000,1064-1073.
[43]F. M. Donini, M. Lenzerini, et al. Reasoning in description logic[J]. Principles of Knowledge Representation,1996,14(02):204-224.
[44]Sirin E,Parsia B,Grau B C, et al. Pellet:A practical OWL-DL reasoner[J]. Journal of Web Semantics,2007,5(2):51-53.
[45]S. Schlobach and R. Cornet. Non-standard reasoning services for the debugging of description logic terminologies[C].8th International Joint Conference on Artificial Intelli-gence, Berlin, 2003,335-362.
[46]A. Artale, E. Franconi. A Temporal Description Logic for Reasoning about Actions and Plans [J]. Artificial Intelligence,2012,10(09):1105-1116.
[47]E. Zolin, http://www.cs.man.ac.uk/-ezolin/dl/.
[48]M. Obitko, http://www.obitko.com/tutorials/ontologies-semantic-web/owl-dl-semantics.html.
[49]N. Guarino and P. Giaretta. Ontologies and knowledge bases:towards a terminological clarification[J]. Towards Very Large Knowledge Bases:Knowledge Building and Knowledge Sharing,1995,12(03):25-32.
[50]D. Lenat and R. Guha. Building large knowledge-based systems:representation and inference in the cyc project[R]. Addison-Wesley, Reading, Massachusetts,1990.
[51]M. Baldoni. Normal multimodal logics:Automatic deduction and logic programming extension[D]. Ph.D. dissertation, Dept. Information, Univ. degli Studi di Torino,1998, ch4:70-81.
[52]M. Baldoni, L. Giordano and A. Martelli. A tableau calculus for multimodal logics and some (un)decidability results[C]. Conf. on Analytic Tableaux Related Methods, Berlin,1998,44-59.
[53]V. Haarslev, R. Moller, et al. Extended Query Facilities for Racer and an Application to Software-Engineering Problems[C].2004 International Workshop on Description Logics, Whistler, BC, Canada, June 2004,148-157.
[54]D. Tsarkov and I. Horrocks. FaCT++ description logic reasoner:System description[C].3rd International Joint Conference on Automated Reasoning, Seattle,2006,292-297.
[55]C. Fellbaum. WordNet:An Electronic Lexical Database[B]. MIT Press,1998, chl:2-5.
[56]G. A. Miller. Wordnet:a lexical database for English[J]. Communication of ACM,1995, 38(11):39-41.
[57]G. A. Miller. Wizard of the new wordsmiths:His idea to link words rewrote the dictionary. Communication of ACM,2002,42(02):39-41.
[58]G. A. Miller, R. Beckwith, et al. Introduction to wordnet-an online lexical database[J]. International Journal of Lexicography,1990,4(3):235-244.
[59]陈群秀.一个在线义类词库：词网WordNet[J].语言文字应用,1998,4(02)：60-67.
[60]姚天顺,张俐WordNet综述[J].语言文字应用,2001,20(03)：58-64.
[61]Y. Kalfoglou and M. Schorlemmer. Ontology mapping:the state of the art[J]. The Knowledge Engineering Review,2003,18(01):1-31.
[62]P. Shvaiko and J. Euzenat. Ten challenges for ontology matching[C]. OTM Confederated International Conferences, Coopis,2008,1922-1930.
[63]S. Bowers and L. Delcambre. Representing and transforming model-based information[C].1st Workshop on the Semantic Web at the Fourth European Conference on Digital Libraries, Lisbon, 2000,144-253.
[64]H. Chalupsky. Ontomorph:A translation system for symbolic logic[C]. KR2000:Principles of Knowledge Representation and Reasoning, San Francisco,2000,471-482.
[65]V. Chaudhri, A. Farquhar, et al. Okbc:A programmatic foundation for knowledge base interoperability[C]. AAAI, Pairs,1998,600-607.
[66]J. Euzenat. Towards a principled approach to semantic interoperability[C]. Workshop on Ontologies and Information Sharing, Seattle,2001,508-517.
[67]S. Melnik and S. Decker. A layered approach to information modeling and interoperability on the web[C]. ECDL 2000 Workshop on the Semantic Web, Lisbon,2000,1004-1011.
[68]M. Klein. Combining and relating ontologies:an analysis of problems and solutions[C]. Workshop on Ontologies and Information Sharing, Seattle,2001,205-211.
[69]A. Doan and Y. Alon. Semantic Integration Research in the Database Community:A Brief SurveyfJ]. AI Magazine,2005,26(01):83-94.
[70]Avigdor Gal. Managing Uncertainty in Schema Matching with Top-K Schema Mappings[J]. Journal on Data Semantics,2006,6(05):90-114.
[71]Alon Y. Halevy. Why Your Data Won't Mix:Semantic Heterogeneity [J]. ACM Queue,2005, 3(8):50-58.
[72]H. Do and E. Rahm. COMA-a system for flexible combination of schema matching approaches[C]. VLDB, Berlin,2002,1901-1910.
[73]Z. Aleksovski. Using background knowledge in ontology matching[D]. Ph.D. dissertation, Vrije Universiteit, Amsterdam,2008, ch05:101-105.
[74]J. Madhavan, P. Bernstein and E. Rahm. Generic schema matching with Cupid[C]. VLDB, Dublin,2001,1302-1311.
[75]H. Zhao. Semantic matching across heterogeneous data sources[J]. Commun. ACM,2007, 50(01):45-50.
[76]Y. Kalfoglou, B. Hu, et al. Capturing, representing and operationalising semantic integration (crosi) project-final report[R]. Electronics & Computer Science EPrints Service-University of Southampton,2005, ch03:35-40.
[77]Choi, Namyoun, S. IlYeol and H. Hyoil. A survey on ontology mapping[C]. SIGMOD Rec., September 2006,34-41.
[78]P.Shvaiko and J.Euzenat. A survey of schema-based matching approaches[J]. Journal on Data Semantics,2005,36(12):146-171.
[79]T. L. Bach, J. D. Bo, et al. Knowledgeweb consortium, state of the art on ontology (d2.2.3)[R]. Knowledge Web Consortium,2004.
[80]S. Melnik, H. Garcia-Molina and E. Rahm. Similarity flooding:A versatile graph matching
algorithm and its application to schema matching[C].18th International Conference on Data Engineering, Dublin,2002,1021-1030.
[81]Y. R. Jean-Mary, E. P. Shironoshita and M. R. Kabuka. Ontology matching with semantic verification[J]. Web Semantics:Science, Services and Agents on the World Wide Web,2009, 7(03):235-251.
[82]Y. R. Jean-mary, E. P. Shironoshita and M. R. Kabuka. Asmov:Results for oaei 2009[EB/OL]. Available:http://www.dit.unitn.it/_p2p/OM-2009/oaei09 paper4.pdf
[83]G. C. W. Hu and X. Z. D. Zheng. The results of falcon-ao in the oaei 2006 campaign. [EB/OL]. Available:http://ww.dit.unitn.it/_p2p/OM-2006/11-Falcon-OAEI%2706.pdf
[84]N. Jian, W. Hu, G. Cheng and Y. Qu. Falcon-ao:Aligning ontologies with falcon[C]. K-Cap 2005 Workshop on Integrating Ontologies, Alaska,2005,87-93.
[85]Y. Qu. Constructing virtual documents for ontology matching[C].15th International World Wide Web Conference, Annapolis,2006,23-31.
[86]Y. Kalfoglou and M. Schorlemmer. If-map:an ontology mapping method based on information flow theory[J]. Journal on Data Semantics, October 2003, 1(01):98-127.
[87]A. Doan, P. Domingos and A. Halevy. Reconciling schemas of disparate data sources:A machine-learning approach[C]. SIGMOD Conference, Albany(NY),2001,509-520.
[88]A. Doan, J. Madhavan, et al. Ontology matching:A machine learning approach[B]. Handbook on Ontologies in Information Systems,2003, ch5:397-416.
[89]A. Doan, J. Madhavan, et al. Learning to map between ontologies on the semantic web[C].11th international conference on World Wide Web, New York,2002.662-673.
[90]J. Tang, J. Li, B. Liang, et al. Using Bayesian decision for ontology mapping[J]. Web Semantics: Science, Services and Agents on the World Wide Web,2006,4(04):243-262.
[91]X. Zhang and Q. Zhong. Rimom results for OAEI 2009[EB/OL], Available: http://www.dit.unitn.it/-p2p/OM-2009/
[92]J. Li, J. Tang, Y. Li and Q. Luo. Rimom:A dynamic multistrategy ontology alignment framework[J]. IEEE Transactions on Knowledge and Data Engineering,2008, 21(02):1218-1232.
[93]S. Albagli, R. Ben-Eliyahu-Zohary and S. E. Shimony. Markov network based ontology matching[J]. Journal of Computer and System Sciences, In Press, Accepted Manuscript,2012.
[94]M. Nagy, M. Vargas-vera and E. Motta. DSSim-ontology Mapping with Uncertainty[C].1st International Workshop on Ontology Matching, Baton Rouge,2006,115-123.
[95]D. J'er^ome, G. Fabrice, et al. Matching directories and OWL ontologies with AROMA[C].15th ACM international conference on Information and knowledge management, Boston,2006, 830-831.
[96]F. Giunchiglia, P. Shvaiko and M. Yatskevich. S-match:an algorithm and an implementation of semantic matching[C]. ESWS, Dublin,2004,61-75.
[97]F. Giunchiglia, P. Shvaiko and M. Yatskevich. Discovering missing background knowledge in ontology matching[C]. ECAI, Chicago,2006,382-386.
[98]P. Shvaiko and A. V. Zhdanova. Semantic matching[J]. The Knowledge Engineering Review, 2003,31(07):341-357.
[99]F. Giunchiglia and M. Yatskevich. Element level semantic matching[C]. Meaning Coordination and Negotiation workshop, Columbia,2004,1021-1029.
[100]O. Udrea, L. Getoor and R. J. Miller. Leveraging data and structure in ontology integration[C]. ACM SIGMOD international conference on Management of data, New York,2007,449-460.
[101]M. B. Antonia, A. Don, et al. Context matching for electronic marketplaces-a case study[C]. Workshop on Ontologies and Distributed Systems, Ottawa,2002,205-209.
[102]Peigang Xu, Yadong Wang and Tianyi Zang. Alignment Results of SOBOM for OAEI 2009[EB/OL]. Available:http://dit.unitn.it/_p2p/OM-2009/oaei10 paper12.pdf
[103]N. F. Noy and M. A. Musen. Evaluating ontology-mapping tools:Requirements and experience[C]. Workshop on Evaluation of Ontology Tools, Siguenza,2002,1024-1030.
[104]G. Stoilos, G. Stamou and S. Kollias. A String Metric for Ontology Alignment[C].4th International SemanticWeb Conference (ISWC2005), Galway,2005,867-871.
[105]W. Robert and G. Schreiber. A Method to Combine Linguistic Ontology-Mapping Techniques[C].4th International Semantic Web Conference, Galway,2005,214-221.
[106]W. Cohen, P. Ravikumar and S. Fienberg. A comparison of string metrics for matching names and records[C]. KDD-2003 Workshop on Data Cleaning, Record Linkage, and Object Consolidation. Washington, Boise,2003,618-624.
[107]M. Ehrig and Y. Sure. FOAM-Framework for Ontology Alignment and Mapping Results of the Ontology Alignment Evaluation Initiative[C]. Integrating Ontologies Workshop, Alberta,2005, 747-751.
[108]唐杰,梁邦勇,李涓子,王克宏.语义Web中的本体自动映射[J].计算机学报,2006,29(11)：1956-1976.
[109]P. Wang and B. Xu. Debugging Ontology Mapping:A Static Method[J]. Computing and Informatics,2008,27(1):21-36.
[110]P. Wang and B. Xu. Using Bridge Ontology for Detailed Semantic Annotation Based on Multi-ontologies[J]. International Journal of Electronics and Computer Science,2004, 6(02):19-29.
[111]W. Peng, B. Xu, et al. Bridge Ontology:A multi-ontologies-based approach for semantic annotation[J]. Wuhan University Journal of Natural Sciences,2004,9(05):617-622.
[112]A. Farquhar, R. Fikes and J. Rice. The ontolingua server:A tool for collaborative ontology construction[C].10th Knowledge Acquisition for Knowledge-based Systems workshop, Hamilton,1996,104-111.
[113]M. Guinness and L. Deborah. Conceptual Modeling for Distributed Ontology Environments[C]. 8th International Conference on Conceptual Structures Logical, Linguistic, and Computational Issues, Darmstadt,2000,14-18.
[114]M. Guinness, L. Deborah, et al. The Chimaera Ontology Environment[C].7th National Conference on Artificial Intelligence, Austin,2000,501-510.
[115]N. F. Noy, S. Kunnatur, et al. Tracking Changes During Ontology Evolution[C].3rd International Conference on the Semantic Web (ISWC-2004), Hisroshima, Japan.
[116]N. F. Noy and M. A. Musen. Ontology Versioning as an Element of an Ontology-Management Framework[J]. IEEE Intelligent Systems, In Press, Accepted Manuscript,2012.
[117]G. Stumme and A. Maedche. Fca-merge:Bottom-up merging of ontologies[C]. International Joint Conference on Artificial Intelligence, Seattle,2001,804-810.
[118]B. Ganter and R. Wille. Formal. Concept Analysis:mathematical foundations[B].1999, ch6:513-518.
[119]J. Bruijn, F. Martin-Recuerda, et al. State-of-the-art survey on ontologymerging and aligning v2 Deliver-able D4·2·2[R]. Semantically Enabled Knowledge Technologies,2005, ch04:212-219
[120]卢胜军,真溱.本体集成相关的基本概念研究[J].信息系统,2008,21(03)：1101-1107.
[121]S. PintoH and G.Perez. Some issueson ontology integration[C]. Workshop on Ontologies and Problem-SolvingMethods. Stock-holm,1999,1452-1459.
[122]黄烟波,张红宇,李建华.本体映射方法研究[J].计算机工程与应用,2005,41(18)：27-33.
[123]潘阳威,徐汀荣,靳涛.语义Web本体匹配算法研究[J].计算机与现代化,2008,18(11)：15-19.
[124]杨宁,郭雷,方俊,杜亚勤.语义Web作为背景知识的本体匹配[J].西安工业大学学报,2011,38(31)：175-180.
[125]费雅洁.粗糙集理论在本体匹配预处理中的应用[J].信息技术,2009,16(04)：44-47.
[126]K. Li, B. Xu, et al. An Ontology Mapping Approach Using Web Search Engine[J]. Journal of Southeast University,2007,23(3):352-356.
[127]S. Zhang, P. Mork, et al. Comparing two approaches for aligning representations of anatomy[J]. Artificial Intelligence in Medicine,2007,39(12):227-236.
[128]李虎,张啸,等.流程可定制本体匹配框架:RiMOM2[J].计算机科学,2011,15(38)：151-160.
[129]李熙,徐德智.本体映射中一种基于WordNet名称策略算法[J].微计算机信息,2009,16(25)：258-161.
[130]H. Wimmer, V. Yoon, et al. Applying Semantic Web Technologies to Ontology Alignment [J]. International Journal of Intelligent Information Technologies,2012,8(01):356-367.
[131]M. Hussain and S. Srivatsa. A Study of Different Ontology Matching System [J]. International Journal of Computer Applications,2012,37(12):0975-8887.
[132]王颖,张汝波,赖积保.本体匹配的形式化描述[J].郑州大学学报,2009,16(41)：19-24.
[133]于晓繁,王效岳,白如江.本体集成方法和工具综述[J].现代图书情报技术,2011,10(101)：12-20.
[134]S. Pavel, J. Euzenat. Ontology Matching:State of the Art and Future Challenges [J]. IEEE Transactions on Knowledge and Data Engineering,2012,99(04):449-460.
[135]M. F. Porter. An algorithm for suffix stripping[B]. Information retrieval,1997, ch5:130-137.
[136]张玉芳,李川,熊忠阳.改进的本体匹配算法[J].计算机应用,2009,16(31)：1067-1071.
[137]W. Cohen, P. Ravikumar and E. Fienberg. A comparison of string metrics for matching names and records[C]. Workshop on Data Cleaning, Record Linkage, and Object Consolidation. Washington, DC,2003,821-829.
[138]何娟,高志强,等.基于词汇相似度的元素级本体匹配[J].计算机工程,2006,11(32)：185-188.
[139]T. Lukasiewicz, L. Predoiu and H. Stuckenschmidt. Tightly integrated probabilistic description logic programs for representing ontology mappings[EB/OL].2012, Available:http://dx.doi.org/10.1007/s 10472-012-9280-3.
[140]张忠平,赵海亮,张志惠.基于OWL的本体集成[J].计算机应用,2008,17(01)：88-94.
[141]P. Mihajlik, Z. Tuske, et al. Improved recognition of spontaneous hungarian speech-morphological and acoustic modeling techniques for a less resourced task[J]. IEEE Transactions on Audio, Speech, and Language Processing,2010,18(06):1588-1600.
[142]张忠平,赵海量,何丽荣.本体中is-a层次的构建和本体集成[J].2008,16(25)：3249-3252.
[143]I. Levenshtein. Binary codes capable of correcting deletions, insertions, and reversals, cybernetics and control theory[J]. Cybernetics and Control Theory,1966,10(08):707-710.
[144]王颖,刘群,等.一种基于RDF的本体匹配方法[J].计算机应用,2008,16(28)：460-463.
[145]S. Liang, Q. Luo, et al. Criteria-Based Approximate Matching of Large-Scale Ontologies[J]. Knowledge Engineering and Management,2012,12(03):283-288.
[146]D. Lin. An information-theoretic definition of similarity[C].15th International Conference of Machinge Learning, Alaska,1998,296-304.
[147]J. Madhavan, P. Bernstein and E. Rahm. Generic Schema Matching with Cupid[J]. VLDB Journal,2001,13(04):49-58.
[148]J. Euzenat, D. Loup, et al. Ontology Alignment with OLA[C].3rd Semantic Web Conference, Hiroshima, November 2004,1104-1110.
[149]T. Pedersen, S. Banerjee and S. Patwardhan. Maximizing semantic relatedness to perform word sense disambiguation [R]. University of Minnesota Supercomputing Institute, Minneapolis, 2005.
[150]S. Patwardhan. Incorporating dictionary and corpus information into a context vector measure of semantic relatedness[D]. Ph.D. dissertation, University of Minnesota, Duluth,2003.
[151]S. Banerjee, T. Pedersen. Extended gloss overlaps as a measure of semantic relatedness[C].8th International Joint Conference on Artificial Intelligence, Acapulco,2003,805-810.
[152]R. Rada, H. Mili, et al. Development and application of a metric on semantic nets[J]. IEEE Transactions on Systems, Man and Cybernetics,2010,19 (01):17-30.
[153]Z. Wu, and M. Palmer. Verb semantics and lexical selection[C].32nd Annual Meeting of the Association for Computational Linguistics, New Mexico,1994,133-138.
[154]G. Hirst, and D. St-Onge. Lexical chains as representations of context for the detection and correction of malapropisms[B]. WordNet:An electronic lexical database,1998, ch2:305-332.
[155]P. Resnik. Using information content to evaluate semantic similarity in a taxonomy[C].14th International Joint Conference on Artificial Intelligence, Montreal,1995,448-453.
[156]J. Jiang, and D. Conrath. Semantic similarity based on corpus statistics and lexical taxonomy[C]. International Conference on Research in Computational Linguistics, Taiwan,1997, 19-33.
[157]仲新宇.一种基于结构相似的本体匹配方法[J].电脑开发与应用,2009,16(22)：1 1-14.
[158]R. Gligorov, Z. Aleksovski, et al. Using Google Distance to Weight Approximate Ontology Matches[C]. Conf. World Wide Web,2007,767-776.
[159]J. Broekstra. Storage, querying and inferencing for semantic web languages[D]. Ph.D. dissertation, Amsterdam, Netherlands, VrijeUniversity,2005, ch2:20-24.
[160]Z. Miao, Y. Zhang, et al. Parallel algorithm ofgenerating closure of RDFS source[J]. Journal of SoutheastUniversity,2006,22(03):435-438.
[161]P. Ziegler, C. Kiefer, et al. Generic Similarity Detection in Ontologies with the SOQASimPack Toolkit[C]. ACM SIGMOD International Conference on Management of Data, Chicago,2006, 36-43.
[162]B. Hollunder and W. Nutt. Subsumption Algorithms for Concept Languages[R]. German Research Center for Artificial Intelligence,1990.
[163]S. Brandt, R. Ksters and T. Anni-Yasmin. Approximating ALCN-Concept Descriptions[R]. Aachen Theoretical Computer Science,2002.
[164]N. Fanizzi and C. d'Amato. A similarity measure for the ALN description logic[C]. Italian Conference on Computational Logic, Milan,2006,26-21.
[165]C. d'Amato, N. Fanizzi and F. Esposito. A dissimilarity measure for ALC concept descriptions [C], SAC, Rome,2006,1695-1699.
[166]李剑.Web知识本体集成[J].计算机科学,2004,13(31)：1-6.
[167]A. Miles and S. Bechhofer. skos simple knowledge organization system reference[S]. w3c proposed recommendation,2009.
[168]C. Meilicke. The relevance of reasoning and alignment incoherence in ontology matching[J]. Computer Science,2009,19(12):934-938.
[169]C. Meilicke, H. Stuckenschmidt and A. Tamilin. Improving automatically created mappings using logical reasoning[R]. University of Mannheim,2009.
[170]H. Stuckenschmidt, L. Serafini and H. Wache. Reasoning about ontology mappings[R]. University of Mannheim, Germany,2005.
[171]C. Meilicke, H. Stuckenschmidt and A. Tamilin. Repairing ontology mappings[C]. AAAI, Detroit,2007,1408-1413.
[172]C. Meilicke and H. Stuckenschmidt. Analyzing mapping extraction approaches[C]. Ontology Matching Workshop, Verona,2007,1205-1210..
[173]W. Huang, J. Yang, et al. Study on Construction of Emergency Plan Ontology Model[J]. Information Technology Journal,2012,11(04):414-419.
[174]C. Trojahn, P. Quaresma, et al. Exploiting Majority Acceptable Arguments for Ontology Matching[J]. International Journal of Artificial Intelligence,2012,3(08):310-321.
[175]于娟,党延忠.本体集成研究综述[J].计算机科学,2008,5(35)：9-15.
[176]赵晋巍,真溱.本体匹配技术研究概述[J].现代图书情报技术,2009,06(185)：5-9.
[177]谢亦才,钟剑,本体匹配概述[J].科技咨询,2009,07(10)：178-180.
[178]A. KORDA and N, KALJA. Storing OWL ontologies inSQL relational databases[J], International Journal of ElectricalComputer and Systems Engineering,2007,1(04):1307-1379.
[179]P. PANTEL, D. LIN. Discovering word senses from text[C]. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Edmonton Alberta,2002,613-619.
[180]M. Haspelmath. The indeterminacy of word segmentation and the nature of morphology and syntax [J]. Folia Linguistica,2011,45(1):31-80.
[181]G. Antoniou and A. Bikakis. DR-Prolog:A system for defeasible reasoning with rules and ontologies on the semantic Web[J]. IEEE Transactions on Knowledge and Data Engineering, 2007,19(02):233-245.
[182]S. Decker, M. Erdmann, et al. Oil in a nutshell[C]. EKAW'00, France,2000,1403-1410.
[183]Y. Qu, G. Cheng. Falcons concept search:A practical search engine for web ontologies [J]. IEEE Transactions on Systems, Man and Cybernetics, Part A:Systems and Humans,2011, 41(4):810-816.
[184]N. James, K. Todorov, et al. Combining visual and textual modalities for multimedia ontology matching [C]. Conference on Semantic Multimedia,2011,95-110.
[185]R. Studer, R. Benjamins, and D. Fensel. Knowledge Engineering:Principles and Methods[J]. Data and Knowledge Engineeing,1998,25(122):161-197.
[186]M. Kolli, Z. Boufaida. A description logics formalization for the ontology matching [J]. Procedia Computer Science,2011,23(03):29-35.
[187]Q. Reul and J. Z. Pan. Kosimap:Use of description logic reasoning to align heterogeneous ontologies[C].23rd International Workshop on Description Logics, Waterloo,2010,537-545.
[2]W. Nico Borst. Construction of Engineering Ontologies for Knowledge Sharing and Reuse[D]. PhD dissertation, Enschede:University of Twente,1997, chl:10-12.
[3]T. Berners-Lee, J. Hendler and O. Lassila. The semantic web[J]. Scientific American,2001, 284(05):34-43.
[4]World Wide Web Consortium (W3C)[EB/OL]. Available:http://www.w3.org/.
[5]Semantic Web[EB/OL]. Available:http://en.wikipedia.org/wiki/Semantic_web.
[6]Ontology (information science)[EB/OL]. Available: http://en.wikipedia.org/wiki/Ontology_information_science.
[7]T. Berners-Lee and J. Hendler. Publishing on the semantic web-the coming Internet revolution will profoundly affect scientific information[J]. Nature,2001,410(6832):1023-1024.
[8]D. Beneventano, S. Bergamaschi, F. Guerra and M. Vincini. Themomis approach to information integration[C].3rd International Conference on Enterprise Information Systems, Portugal,2001, 1082-1086.
[9]S. Bergamaschi, S. Castano and M. Vincini. Semantic integration of semi-structured and structured data sources[C]. SIGMOD Record, Enschede,1999,54-59.
[10]S. Bergamaschi, F. Guerra and M. Vincini. A data integration framework for e-commerce product classification[C].1st semantic web conference, London,2002,379-393.
[11]S. Albagli, R. Ben-Eliyahu-Zohary and S. E. Shimony. Markov network based ontology matching[J]. Journal of Computer and System Sciences, In Press, Accepted Manuscript,2012.
[12]M. Obitko, Translation between Ontologies in Multi-Agent Systems[EB/OL]. Available:http://keg.vse.cz/_slides/obitko-2007.pdf
[13]Xiaomeng Su. Sematnic Enrichment for ontology mapping[D]. Ph.D. dissertation, Dept. Electron.Eng., Norwegian Univ. of Seience and Technology,2004, ch3:40-45.
[14]郑晓庆.语义万维网的不确定知识表示与信任计算[D].浙江大学博士学位论文,2007,ch2：20-14.
[15]周丽平.DL-Lite本体的不一致处理方法研究[D].北京交通大学博士学位论文,201,ch3：30-35.
[16]徐凯丰.中文语义万维网本体匹配[D].上海交通大学博士学位论文,2010,ch2：19-25.
[17]汪鹏.本体映射关键问题研究[D].东南大学博士学位论文,2008,ch3：28-34.
[18]W. Nico Borst. Construction of Engineering Ontologies for Knowledge Sharing and ReusefD]. Ph.D. dissertation, Enschede University of Twente,1997, ch2:22-28.
[19]R. Studer, R. Benjamins and D. Fensel. Knowledge Engineering:Principles and Methods[J]. Data and Knowledge Engineeing,1998,25(122):161-197.
[20]I. Horrocks, P. F. Patel-Schneider and F. V. Harmelen. From shiq and rdf to owl:The making of a web ontology language[J]. Journal of Web Semantics,2003,17(01):19-29.
[21]F. Baader, D. Calvanese, et al. The Description Logic Handbook:Theory, Implementation and Applications[B]. Cambridge University Press,2003, ch2:46-99.
[22]K. Shafa'amri and J. Atoum. A Framework for Improving the Performance of Ontology Matching Techniques in Semantic Web[J]. International Journal of Advanced Computer Science and Application,2012,03(01):10-21.
[23]M. PREECE and A,GRAY P. Implementing a semanticWeb blackboard system using Jena[EB/OL]. Available:http://eprints.aktors.org/569/01/ImplSWBbUsingJena juc2006.pdf.
[24]X. Su and L. Ilebrekke. A comparative study of ontology languages and tools[C].7th IFIP-WG8.1 International Workshop on Evaluating of Modeling Methods in Systems Analysis and Design, Pairs,2002,1120-1126.
[25]X. Su and L. Ilebrekke. Using a semiotic framework for a comparative study of ontology languages and tools[J]. Information Modeling Methods and Methodologies,2004, 15(08):1102-1120.
[26]S. Luke and J. Heflin. Shoe, the proposed specification, shoe project[EB/OL]. Available:http://www.cs.umd.edu/projects/plus/SHOE/spec.html,2000.
[27]J. Heflin, J. Hendler, and S. Luke. Coping with changing ontologies in a distributed environment[C]. AAAI workshop on ontology management, San Francisco,1999,402-410.
[28]D. Fensel, M. Crubezy, et al. Oil &upml:A unifying framework for the knowledge web[C]. ECAI, Berlin, Germany,2000,1087-1098.
[29]M. Kolli and Z. Boufaida. A description logics formalization for the ontology matching[J]. Procedia Computer Science,2011,3(01):29-35.
[30]O. Lassila and R. Swick. Resource description framework (rdf) model and syntax specification [S]. w3c recommendation,1999.
[31]D. Brickley and R. Guha. Resource description framework schema specification 1.0[S]. w3c recommendation,2000.
[32]T. Bray, J. Paoli, et al. Extensible markup language (xml) 1.0 (second edition)[S]. w3c recommendation,2000.
[33]I. Horrocks, P. F. Patel-Schneider and F. van Harmelen. Reviewing the design of daml+oil:An ontology language for the semantic web[C]. AAAI, Mecigo,2002,792-797.
[34]I. Horrocks, F. van Harmelen and P. F. Patel-Schneider. Reference description of the daml+oil ontology markup language[EB/OL]. Available:http://www.daml.org/2001/03/reference.html.
[35]M. Kifer, G. Lausen and J. Wu. Logical foundations of object oriented and frame-based languages[J]. Journal of Computer Technologies,1995,12(05):185-200.
[36]D. McGuinness and F. van Harmelen eds. Owl web ontology language overview[S]. w3c proposed recommendation,2003.
[37]F. Harmelen, J. Hendler, et al. OWL Web Ontology Language Reference[EB/OL]. Available:http://www.w3.org/TR/2004/REC-owl-ref-20040210.2004.
[38]卢刘明,朱国进,陈家训.语义Web中几种语义描述语言的分析比较[J].计算机工程,2005,20(03)：1086-1092.
[39]胡鹤,刘大有,王生生.Web本体语言的分析与比较[J].计算机工程,2005,12(04)：870-876.
[40]R. MacGregor. Using a description classifier to enhance deductive inference[C].7th IEEE Conference on AI Application, Florida,1991,93-97.
[41]R. S. Cost, T. Finin, et al. ITTalks:A Case Study in the Semantic Web and DAML[EB/OL]. Available:http://www.semanticweb.org/SWWS/program/full/paper41.pdf
[42]T. Finin, W. Krueger, et al. Automatically Generated DAML Markup for Semistructured Documents[C]. AAAI Spring Symposium on Agent-Mediated Knowledge Management, Manchester,2000,1064-1073.
[43]F. M. Donini, M. Lenzerini, et al. Reasoning in description logic[J]. Principles of Knowledge Representation,1996,14(02):204-224.
[44]Sirin E,Parsia B,Grau B C, et al. Pellet:A practical OWL-DL reasoner[J]. Journal of Web Semantics,2007,5(2):51-53.
[45]S. Schlobach and R. Cornet. Non-standard reasoning services for the debugging of description logic terminologies[C].8th International Joint Conference on Artificial Intelli-gence, Berlin, 2003,335-362.
[46]A. Artale, E. Franconi. A Temporal Description Logic for Reasoning about Actions and Plans [J]. Artificial Intelligence,2012,10(09):1105-1116.
[47]E. Zolin, http://www.cs.man.ac.uk/-ezolin/dl/.
[48]M. Obitko, http://www.obitko.com/tutorials/ontologies-semantic-web/owl-dl-semantics.html.
[49]N. Guarino and P. Giaretta. Ontologies and knowledge bases:towards a terminological clarification[J]. Towards Very Large Knowledge Bases:Knowledge Building and Knowledge Sharing,1995,12(03):25-32.
[50]D. Lenat and R. Guha. Building large knowledge-based systems:representation and inference in the cyc project[R]. Addison-Wesley, Reading, Massachusetts,1990.
[51]M. Baldoni. Normal multimodal logics:Automatic deduction and logic programming extension[D]. Ph.D. dissertation, Dept. Information, Univ. degli Studi di Torino,1998, ch4:70-81.
[52]M. Baldoni, L. Giordano and A. Martelli. A tableau calculus for multimodal logics and some (un)decidability results[C]. Conf. on Analytic Tableaux Related Methods, Berlin,1998,44-59.
[53]V. Haarslev, R. Moller, et al. Extended Query Facilities for Racer and an Application to Software-Engineering Problems[C].2004 International Workshop on Description Logics, Whistler, BC, Canada, June 2004,148-157.
[54]D. Tsarkov and I. Horrocks. FaCT++ description logic reasoner:System description[C].3rd International Joint Conference on Automated Reasoning, Seattle,2006,292-297.
[55]C. Fellbaum. WordNet:An Electronic Lexical Database[B]. MIT Press,1998, chl:2-5.
[56]G. A. Miller. Wordnet:a lexical database for English[J]. Communication of ACM,1995, 38(11):39-41.
[57]G. A. Miller. Wizard of the new wordsmiths:His idea to link words rewrote the dictionary. Communication of ACM,2002,42(02):39-41.
[58]G. A. Miller, R. Beckwith, et al. Introduction to wordnet-an online lexical database[J]. International Journal of Lexicography,1990,4(3):235-244.
[59]陈群秀.一个在线义类词库：词网WordNet[J].语言文字应用,1998,4(02)：60-67.
[60]姚天顺,张俐WordNet综述[J].语言文字应用,2001,20(03)：58-64.
[61]Y. Kalfoglou and M. Schorlemmer. Ontology mapping:the state of the art[J]. The Knowledge Engineering Review,2003,18(01):1-31.
[62]P. Shvaiko and J. Euzenat. Ten challenges for ontology matching[C]. OTM Confederated International Conferences, Coopis,2008,1922-1930.
[63]S. Bowers and L. Delcambre. Representing and transforming model-based information[C].1st Workshop on the Semantic Web at the Fourth European Conference on Digital Libraries, Lisbon, 2000,144-253.
[64]H. Chalupsky. Ontomorph:A translation system for symbolic logic[C]. KR2000:Principles of Knowledge Representation and Reasoning, San Francisco,2000,471-482.
[65]V. Chaudhri, A. Farquhar, et al. Okbc:A programmatic foundation for knowledge base interoperability[C]. AAAI, Pairs,1998,600-607.
[66]J. Euzenat. Towards a principled approach to semantic interoperability[C]. Workshop on Ontologies and Information Sharing, Seattle,2001,508-517.
[67]S. Melnik and S. Decker. A layered approach to information modeling and interoperability on the web[C]. ECDL 2000 Workshop on the Semantic Web, Lisbon,2000,1004-1011.
[68]M. Klein. Combining and relating ontologies:an analysis of problems and solutions[C]. Workshop on Ontologies and Information Sharing, Seattle,2001,205-211.
[69]A. Doan and Y. Alon. Semantic Integration Research in the Database Community:A Brief SurveyfJ]. AI Magazine,2005,26(01):83-94.
[70]Avigdor Gal. Managing Uncertainty in Schema Matching with Top-K Schema Mappings[J]. Journal on Data Semantics,2006,6(05):90-114.
[71]Alon Y. Halevy. Why Your Data Won't Mix:Semantic Heterogeneity [J]. ACM Queue,2005, 3(8):50-58.
[72]H. Do and E. Rahm. COMA-a system for flexible combination of schema matching approaches[C]. VLDB, Berlin,2002,1901-1910.
[73]Z. Aleksovski. Using background knowledge in ontology matching[D]. Ph.D. dissertation, Vrije Universiteit, Amsterdam,2008, ch05:101-105.
[74]J. Madhavan, P. Bernstein and E. Rahm. Generic schema matching with Cupid[C]. VLDB, Dublin,2001,1302-1311.
[75]H. Zhao. Semantic matching across heterogeneous data sources[J]. Commun. ACM,2007, 50(01):45-50.
[76]Y. Kalfoglou, B. Hu, et al. Capturing, representing and operationalising semantic integration (crosi) project-final report[R]. Electronics & Computer Science EPrints Service-University of Southampton,2005, ch03:35-40.
[77]Choi, Namyoun, S. IlYeol and H. Hyoil. A survey on ontology mapping[C]. SIGMOD Rec., September 2006,34-41.
[78]P.Shvaiko and J.Euzenat. A survey of schema-based matching approaches[J]. Journal on Data Semantics,2005,36(12):146-171.
[79]T. L. Bach, J. D. Bo, et al. Knowledgeweb consortium, state of the art on ontology (d2.2.3)[R]. Knowledge Web Consortium,2004.
[80]S. Melnik, H. Garcia-Molina and E. Rahm. Similarity flooding:A versatile graph matching
algorithm and its application to schema matching[C].18th International Conference on Data Engineering, Dublin,2002,1021-1030.
[81]Y. R. Jean-Mary, E. P. Shironoshita and M. R. Kabuka. Ontology matching with semantic verification[J]. Web Semantics:Science, Services and Agents on the World Wide Web,2009, 7(03):235-251.
[82]Y. R. Jean-mary, E. P. Shironoshita and M. R. Kabuka. Asmov:Results for oaei 2009[EB/OL]. Available:http://www.dit.unitn.it/_p2p/OM-2009/oaei09 paper4.pdf
[83]G. C. W. Hu and X. Z. D. Zheng. The results of falcon-ao in the oaei 2006 campaign. [EB/OL]. Available:http://ww.dit.unitn.it/_p2p/OM-2006/11-Falcon-OAEI%2706.pdf
[84]N. Jian, W. Hu, G. Cheng and Y. Qu. Falcon-ao:Aligning ontologies with falcon[C]. K-Cap 2005 Workshop on Integrating Ontologies, Alaska,2005,87-93.
[85]Y. Qu. Constructing virtual documents for ontology matching[C].15th International World Wide Web Conference, Annapolis,2006,23-31.
[86]Y. Kalfoglou and M. Schorlemmer. If-map:an ontology mapping method based on information flow theory[J]. Journal on Data Semantics, October 2003, 1(01):98-127.
[87]A. Doan, P. Domingos and A. Halevy. Reconciling schemas of disparate data sources:A machine-learning approach[C]. SIGMOD Conference, Albany(NY),2001,509-520.
[88]A. Doan, J. Madhavan, et al. Ontology matching:A machine learning approach[B]. Handbook on Ontologies in Information Systems,2003, ch5:397-416.
[89]A. Doan, J. Madhavan, et al. Learning to map between ontologies on the semantic web[C].11th international conference on World Wide Web, New York,2002.662-673.
[90]J. Tang, J. Li, B. Liang, et al. Using Bayesian decision for ontology mapping[J]. Web Semantics: Science, Services and Agents on the World Wide Web,2006,4(04):243-262.
[91]X. Zhang and Q. Zhong. Rimom results for OAEI 2009[EB/OL], Available: http://www.dit.unitn.it/-p2p/OM-2009/
[92]J. Li, J. Tang, Y. Li and Q. Luo. Rimom:A dynamic multistrategy ontology alignment framework[J]. IEEE Transactions on Knowledge and Data Engineering,2008, 21(02):1218-1232.
[93]S. Albagli, R. Ben-Eliyahu-Zohary and S. E. Shimony. Markov network based ontology matching[J]. Journal of Computer and System Sciences, In Press, Accepted Manuscript,2012.
[94]M. Nagy, M. Vargas-vera and E. Motta. DSSim-ontology Mapping with Uncertainty[C].1st International Workshop on Ontology Matching, Baton Rouge,2006,115-123.
[95]D. J'er^ome, G. Fabrice, et al. Matching directories and OWL ontologies with AROMA[C].15th ACM international conference on Information and knowledge management, Boston,2006, 830-831.
[96]F. Giunchiglia, P. Shvaiko and M. Yatskevich. S-match:an algorithm and an implementation of semantic matching[C]. ESWS, Dublin,2004,61-75.
[97]F. Giunchiglia, P. Shvaiko and M. Yatskevich. Discovering missing background knowledge in ontology matching[C]. ECAI, Chicago,2006,382-386.
[98]P. Shvaiko and A. V. Zhdanova. Semantic matching[J]. The Knowledge Engineering Review, 2003,31(07):341-357.
[99]F. Giunchiglia and M. Yatskevich. Element level semantic matching[C]. Meaning Coordination and Negotiation workshop, Columbia,2004,1021-1029.
[100]O. Udrea, L. Getoor and R. J. Miller. Leveraging data and structure in ontology integration[C]. ACM SIGMOD international conference on Management of data, New York,2007,449-460.
[101]M. B. Antonia, A. Don, et al. Context matching for electronic marketplaces-a case study[C]. Workshop on Ontologies and Distributed Systems, Ottawa,2002,205-209.
[102]Peigang Xu, Yadong Wang and Tianyi Zang. Alignment Results of SOBOM for OAEI 2009[EB/OL]. Available:http://dit.unitn.it/_p2p/OM-2009/oaei10 paper12.pdf
[103]N. F. Noy and M. A. Musen. Evaluating ontology-mapping tools:Requirements and experience[C]. Workshop on Evaluation of Ontology Tools, Siguenza,2002,1024-1030.
[104]G. Stoilos, G. Stamou and S. Kollias. A String Metric for Ontology Alignment[C].4th International SemanticWeb Conference (ISWC2005), Galway,2005,867-871.
[105]W. Robert and G. Schreiber. A Method to Combine Linguistic Ontology-Mapping Techniques[C].4th International Semantic Web Conference, Galway,2005,214-221.
[106]W. Cohen, P. Ravikumar and S. Fienberg. A comparison of string metrics for matching names and records[C]. KDD-2003 Workshop on Data Cleaning, Record Linkage, and Object Consolidation. Washington, Boise,2003,618-624.
[107]M. Ehrig and Y. Sure. FOAM-Framework for Ontology Alignment and Mapping Results of the Ontology Alignment Evaluation Initiative[C]. Integrating Ontologies Workshop, Alberta,2005, 747-751.
[108]唐杰,梁邦勇,李涓子,王克宏.语义Web中的本体自动映射[J].计算机学报,2006,29(11)：1956-1976.
[109]P. Wang and B. Xu. Debugging Ontology Mapping:A Static Method[J]. Computing and Informatics,2008,27(1):21-36.
[110]P. Wang and B. Xu. Using Bridge Ontology for Detailed Semantic Annotation Based on Multi-ontologies[J]. International Journal of Electronics and Computer Science,2004, 6(02):19-29.
[111]W. Peng, B. Xu, et al. Bridge Ontology:A multi-ontologies-based approach for semantic annotation[J]. Wuhan University Journal of Natural Sciences,2004,9(05):617-622.
[112]A. Farquhar, R. Fikes and J. Rice. The ontolingua server:A tool for collaborative ontology construction[C].10th Knowledge Acquisition for Knowledge-based Systems workshop, Hamilton,1996,104-111.
[113]M. Guinness and L. Deborah. Conceptual Modeling for Distributed Ontology Environments[C]. 8th International Conference on Conceptual Structures Logical, Linguistic, and Computational Issues, Darmstadt,2000,14-18.
[114]M. Guinness, L. Deborah, et al. The Chimaera Ontology Environment[C].7th National Conference on Artificial Intelligence, Austin,2000,501-510.
[115]N. F. Noy, S. Kunnatur, et al. Tracking Changes During Ontology Evolution[C].3rd International Conference on the Semantic Web (ISWC-2004), Hisroshima, Japan.
[116]N. F. Noy and M. A. Musen. Ontology Versioning as an Element of an Ontology-Management Framework[J]. IEEE Intelligent Systems, In Press, Accepted Manuscript,2012.
[117]G. Stumme and A. Maedche. Fca-merge:Bottom-up merging of ontologies[C]. International Joint Conference on Artificial Intelligence, Seattle,2001,804-810.
[118]B. Ganter and R. Wille. Formal. Concept Analysis:mathematical foundations[B].1999, ch6:513-518.
[119]J. Bruijn, F. Martin-Recuerda, et al. State-of-the-art survey on ontologymerging and aligning v2 Deliver-able D4·2·2[R]. Semantically Enabled Knowledge Technologies,2005, ch04:212-219
[120]卢胜军,真溱.本体集成相关的基本概念研究[J].信息系统,2008,21(03)：1101-1107.
[121]S. PintoH and G.Perez. Some issueson ontology integration[C]. Workshop on Ontologies and Problem-SolvingMethods. Stock-holm,1999,1452-1459.
[122]黄烟波,张红宇,李建华.本体映射方法研究[J].计算机工程与应用,2005,41(18)：27-33.
[123]潘阳威,徐汀荣,靳涛.语义Web本体匹配算法研究[J].计算机与现代化,2008,18(11)：15-19.
[124]杨宁,郭雷,方俊,杜亚勤.语义Web作为背景知识的本体匹配[J].西安工业大学学报,2011,38(31)：175-180.
[125]费雅洁.粗糙集理论在本体匹配预处理中的应用[J].信息技术,2009,16(04)：44-47.
[126]K. Li, B. Xu, et al. An Ontology Mapping Approach Using Web Search Engine[J]. Journal of Southeast University,2007,23(3):352-356.
[127]S. Zhang, P. Mork, et al. Comparing two approaches for aligning representations of anatomy[J]. Artificial Intelligence in Medicine,2007,39(12):227-236.
[128]李虎,张啸,等.流程可定制本体匹配框架:RiMOM2[J].计算机科学,2011,15(38)：151-160.
[129]李熙,徐德智.本体映射中一种基于WordNet名称策略算法[J].微计算机信息,2009,16(25)：258-161.
[130]H. Wimmer, V. Yoon, et al. Applying Semantic Web Technologies to Ontology Alignment [J]. International Journal of Intelligent Information Technologies,2012,8(01):356-367.
[131]M. Hussain and S. Srivatsa. A Study of Different Ontology Matching System [J]. International Journal of Computer Applications,2012,37(12):0975-8887.
[132]王颖,张汝波,赖积保.本体匹配的形式化描述[J].郑州大学学报,2009,16(41)：19-24.
[133]于晓繁,王效岳,白如江.本体集成方法和工具综述[J].现代图书情报技术,2011,10(101)：12-20.
[134]S. Pavel, J. Euzenat. Ontology Matching:State of the Art and Future Challenges [J]. IEEE Transactions on Knowledge and Data Engineering,2012,99(04):449-460.
[135]M. F. Porter. An algorithm for suffix stripping[B]. Information retrieval,1997, ch5:130-137.
[136]张玉芳,李川,熊忠阳.改进的本体匹配算法[J].计算机应用,2009,16(31)：1067-1071.
[137]W. Cohen, P. Ravikumar and E. Fienberg. A comparison of string metrics for matching names and records[C]. Workshop on Data Cleaning, Record Linkage, and Object Consolidation. Washington, DC,2003,821-829.
[138]何娟,高志强,等.基于词汇相似度的元素级本体匹配[J].计算机工程,2006,11(32)：185-188.
[139]T. Lukasiewicz, L. Predoiu and H. Stuckenschmidt. Tightly integrated probabilistic description logic programs for representing ontology mappings[EB/OL].2012, Available:http://dx.doi.org/10.1007/s 10472-012-9280-3.
[140]张忠平,赵海亮,张志惠.基于OWL的本体集成[J].计算机应用,2008,17(01)：88-94.
[141]P. Mihajlik, Z. Tuske, et al. Improved recognition of spontaneous hungarian speech-morphological and acoustic modeling techniques for a less resourced task[J]. IEEE Transactions on Audio, Speech, and Language Processing,2010,18(06):1588-1600.
[142]张忠平,赵海量,何丽荣.本体中is-a层次的构建和本体集成[J].2008,16(25)：3249-3252.
[143]I. Levenshtein. Binary codes capable of correcting deletions, insertions, and reversals, cybernetics and control theory[J]. Cybernetics and Control Theory,1966,10(08):707-710.
[144]王颖,刘群,等.一种基于RDF的本体匹配方法[J].计算机应用,2008,16(28)：460-463.
[145]S. Liang, Q. Luo, et al. Criteria-Based Approximate Matching of Large-Scale Ontologies[J]. Knowledge Engineering and Management,2012,12(03):283-288.
[146]D. Lin. An information-theoretic definition of similarity[C].15th International Conference of Machinge Learning, Alaska,1998,296-304.
[147]J. Madhavan, P. Bernstein and E. Rahm. Generic Schema Matching with Cupid[J]. VLDB Journal,2001,13(04):49-58.
[148]J. Euzenat, D. Loup, et al. Ontology Alignment with OLA[C].3rd Semantic Web Conference, Hiroshima, November 2004,1104-1110.
[149]T. Pedersen, S. Banerjee and S. Patwardhan. Maximizing semantic relatedness to perform word sense disambiguation [R]. University of Minnesota Supercomputing Institute, Minneapolis, 2005.
[150]S. Patwardhan. Incorporating dictionary and corpus information into a context vector measure of semantic relatedness[D]. Ph.D. dissertation, University of Minnesota, Duluth,2003.
[151]S. Banerjee, T. Pedersen. Extended gloss overlaps as a measure of semantic relatedness[C].8th International Joint Conference on Artificial Intelligence, Acapulco,2003,805-810.
[152]R. Rada, H. Mili, et al. Development and application of a metric on semantic nets[J]. IEEE Transactions on Systems, Man and Cybernetics,2010,19 (01):17-30.
[153]Z. Wu, and M. Palmer. Verb semantics and lexical selection[C].32nd Annual Meeting of the Association for Computational Linguistics, New Mexico,1994,133-138.
[154]G. Hirst, and D. St-Onge. Lexical chains as representations of context for the detection and correction of malapropisms[B]. WordNet:An electronic lexical database,1998, ch2:305-332.
[155]P. Resnik. Using information content to evaluate semantic similarity in a taxonomy[C].14th International Joint Conference on Artificial Intelligence, Montreal,1995,448-453.
[156]J. Jiang, and D. Conrath. Semantic similarity based on corpus statistics and lexical taxonomy[C]. International Conference on Research in Computational Linguistics, Taiwan,1997, 19-33.
[157]仲新宇.一种基于结构相似的本体匹配方法[J].电脑开发与应用,2009,16(22)：1 1-14.
[158]R. Gligorov, Z. Aleksovski, et al. Using Google Distance to Weight Approximate Ontology Matches[C]. Conf. World Wide Web,2007,767-776.
[159]J. Broekstra. Storage, querying and inferencing for semantic web languages[D]. Ph.D. dissertation, Amsterdam, Netherlands, VrijeUniversity,2005, ch2:20-24.
[160]Z. Miao, Y. Zhang, et al. Parallel algorithm ofgenerating closure of RDFS source[J]. Journal of SoutheastUniversity,2006,22(03):435-438.
[161]P. Ziegler, C. Kiefer, et al. Generic Similarity Detection in Ontologies with the SOQASimPack Toolkit[C]. ACM SIGMOD International Conference on Management of Data, Chicago,2006, 36-43.
[162]B. Hollunder and W. Nutt. Subsumption Algorithms for Concept Languages[R]. German Research Center for Artificial Intelligence,1990.
[163]S. Brandt, R. Ksters and T. Anni-Yasmin. Approximating ALCN-Concept Descriptions[R]. Aachen Theoretical Computer Science,2002.
[164]N. Fanizzi and C. d'Amato. A similarity measure for the ALN description logic[C]. Italian Conference on Computational Logic, Milan,2006,26-21.
[165]C. d'Amato, N. Fanizzi and F. Esposito. A dissimilarity measure for ALC concept descriptions [C], SAC, Rome,2006,1695-1699.
[166]李剑.Web知识本体集成[J].计算机科学,2004,13(31)：1-6.
[167]A. Miles and S. Bechhofer. skos simple knowledge organization system reference[S]. w3c proposed recommendation,2009.
[168]C. Meilicke. The relevance of reasoning and alignment incoherence in ontology matching[J]. Computer Science,2009,19(12):934-938.
[169]C. Meilicke, H. Stuckenschmidt and A. Tamilin. Improving automatically created mappings using logical reasoning[R]. University of Mannheim,2009.
[170]H. Stuckenschmidt, L. Serafini and H. Wache. Reasoning about ontology mappings[R]. University of Mannheim, Germany,2005.
[171]C. Meilicke, H. Stuckenschmidt and A. Tamilin. Repairing ontology mappings[C]. AAAI, Detroit,2007,1408-1413.
[172]C. Meilicke and H. Stuckenschmidt. Analyzing mapping extraction approaches[C]. Ontology Matching Workshop, Verona,2007,1205-1210..
[173]W. Huang, J. Yang, et al. Study on Construction of Emergency Plan Ontology Model[J]. Information Technology Journal,2012,11(04):414-419.
[174]C. Trojahn, P. Quaresma, et al. Exploiting Majority Acceptable Arguments for Ontology Matching[J]. International Journal of Artificial Intelligence,2012,3(08):310-321.
[175]于娟,党延忠.本体集成研究综述[J].计算机科学,2008,5(35)：9-15.
[176]赵晋巍,真溱.本体匹配技术研究概述[J].现代图书情报技术,2009,06(185)：5-9.
[177]谢亦才,钟剑,本体匹配概述[J].科技咨询,2009,07(10)：178-180.
[178]A. KORDA and N, KALJA. Storing OWL ontologies inSQL relational databases[J], International Journal of ElectricalComputer and Systems Engineering,2007,1(04):1307-1379.
[179]P. PANTEL, D. LIN. Discovering word senses from text[C]. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Edmonton Alberta,2002,613-619.
[180]M. Haspelmath. The indeterminacy of word segmentation and the nature of morphology and syntax [J]. Folia Linguistica,2011,45(1):31-80.
[181]G. Antoniou and A. Bikakis. DR-Prolog:A system for defeasible reasoning with rules and ontologies on the semantic Web[J]. IEEE Transactions on Knowledge and Data Engineering, 2007,19(02):233-245.
[182]S. Decker, M. Erdmann, et al. Oil in a nutshell[C]. EKAW'00, France,2000,1403-1410.
[183]Y. Qu, G. Cheng. Falcons concept search:A practical search engine for web ontologies [J]. IEEE Transactions on Systems, Man and Cybernetics, Part A:Systems and Humans,2011, 41(4):810-816.
[184]N. James, K. Todorov, et al. Combining visual and textual modalities for multimedia ontology matching [C]. Conference on Semantic Multimedia,2011,95-110.
[185]R. Studer, R. Benjamins, and D. Fensel. Knowledge Engineering:Principles and Methods[J]. Data and Knowledge Engineeing,1998,25(122):161-197.
[186]M. Kolli, Z. Boufaida. A description logics formalization for the ontology matching [J]. Procedia Computer Science,2011,23(03):29-35.
[187]Q. Reul and J. Z. Pan. Kosimap:Use of description logic reasoning to align heterogeneous ontologies[C].23rd International Workshop on Description Logics, Waterloo,2010,537-545.
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