语义网服务中基于机器学习的本体映射研究
|
摘要
语义网(Semantic Web)是在本体(Ontology)理论基础之上对现有Web所进行的扩展,其目标是使Web上的信息具有计算机可以理解的语义,在本体的支持下实现信息系统问语义上的互操作,以及对Web资源所进行的智能访问和检索。语义网服务是以语义网和本体为基础的一个重要的基础研究领域,其目标是通过将语义网技术和Web服务技术相结合,提供下一代网络的集成技术。因此,本体在语义网服务中起了重要的作用。
语义网服务中大量的本体是由不同组织各自独立开发的,其结构和概念的表达形式存在着一定的差异,造成了本体的异构性。本体映射,也称本体匹配。通过本体映射,可以在多个本体之间找到语义相同或相似的对应元素,从而在多个本体之间建立语义联系,消除不同本体或本体不同版本之间知识表达时的不一致现象,进而达到真正意义上的知识共享。因此,本体映射是解决不同本体间的知识共享和重用问题的有效方法。
目前本体映射大多是由人工手动来完成的,不仅过程烦杂,而且很容易出错。这极大地影响了本体映射自动化程度和准确性。本论文针对上述问题,综合考虑了语义网服务中本体的各种异构现象,在对比分析了本体映射各种方法的基础上,重点研究了基于机器学习技术的本体映射机制,提出了一种适用于语义网服务环境的本体映射方法及系统框架,该方法利用机器学习技术来提高本体映射的自动化程度,利用综合评判技术修正映射结果,提高本体映射的准确率,从而有效地解决语义网服务中的本体异构问题。
The Semantic Web is the expansion of existing Web, its goal is to enable the information on the Web have semantics which computer can understand, to achieve semantic interoperability in information systems. Semantic Web Services is an important basic research field based on Semantic Web and the ontology theory, its goal is to integrate Semantic Web and Web Services technology to next-generation network. Therefore, ontology plays an important role in Semantic Web Services.
A large number of ontologies in Semantic Web Services is developed by different organizations independently, there is a certain degree of difference in their structure and expression of concepts, it caused the heterogeneity of ontologies. Ontology mapping, also known as ontology matching. By ontology mapping, the same or similar elements can be found in a number of ontologies, thus the semantics contact among a number of ontologies can be established and inconsistency of knowledge expression in different ontologies can be eliminated. Therefore, ontology mapping is an effective method of solving the problem of knowledge sharing and ontology heterogeneity.
At present, most of the ontology mappings are carried out artificially, the process is not only complex, but also prone to error. To address the above problem, this paper considered th e heterogeneous phenomenon of ontology in Semantic Web Services, compared and analyzed various methods of ontology mapping, studied ontology mapping mechanism based on machine learning technology, proposed efficient ontology mapping method and system framework for the ontologies in Semantic Web Services. The method adopts machine learning techniques to enhance the degree of automation ontology mapping, uses comprehensive evaluation technology to amend the results of ontology mapping, with the result of improving the accuracy of ontology mapping. So as to eliminate the ontology heterogeneity in the Semantic Web Service effectively.
语义网服务中大量的本体是由不同组织各自独立开发的,其结构和概念的表达形式存在着一定的差异,造成了本体的异构性。本体映射,也称本体匹配。通过本体映射,可以在多个本体之间找到语义相同或相似的对应元素,从而在多个本体之间建立语义联系,消除不同本体或本体不同版本之间知识表达时的不一致现象,进而达到真正意义上的知识共享。因此,本体映射是解决不同本体间的知识共享和重用问题的有效方法。
目前本体映射大多是由人工手动来完成的,不仅过程烦杂,而且很容易出错。这极大地影响了本体映射自动化程度和准确性。本论文针对上述问题,综合考虑了语义网服务中本体的各种异构现象,在对比分析了本体映射各种方法的基础上,重点研究了基于机器学习技术的本体映射机制,提出了一种适用于语义网服务环境的本体映射方法及系统框架,该方法利用机器学习技术来提高本体映射的自动化程度,利用综合评判技术修正映射结果,提高本体映射的准确率,从而有效地解决语义网服务中的本体异构问题。
The Semantic Web is the expansion of existing Web, its goal is to enable the information on the Web have semantics which computer can understand, to achieve semantic interoperability in information systems. Semantic Web Services is an important basic research field based on Semantic Web and the ontology theory, its goal is to integrate Semantic Web and Web Services technology to next-generation network. Therefore, ontology plays an important role in Semantic Web Services.
A large number of ontologies in Semantic Web Services is developed by different organizations independently, there is a certain degree of difference in their structure and expression of concepts, it caused the heterogeneity of ontologies. Ontology mapping, also known as ontology matching. By ontology mapping, the same or similar elements can be found in a number of ontologies, thus the semantics contact among a number of ontologies can be established and inconsistency of knowledge expression in different ontologies can be eliminated. Therefore, ontology mapping is an effective method of solving the problem of knowledge sharing and ontology heterogeneity.
At present, most of the ontology mappings are carried out artificially, the process is not only complex, but also prone to error. To address the above problem, this paper considered th e heterogeneous phenomenon of ontology in Semantic Web Services, compared and analyzed various methods of ontology mapping, studied ontology mapping mechanism based on machine learning technology, proposed efficient ontology mapping method and system framework for the ontologies in Semantic Web Services. The method adopts machine learning techniques to enhance the degree of automation ontology mapping, uses comprehensive evaluation technology to amend the results of ontology mapping, with the result of improving the accuracy of ontology mapping. So as to eliminate the ontology heterogeneity in the Semantic Web Service effectively.
引文
[1] Uschold M. Creating, integrating, and maintaining local and global ontologies[A]. In Proceedings of the First Workshop on Ontology Learning (OL-2000) in conjunction with the 14th European Conference on Artificial Intelligence (ECAI-2000), Berlin, Germany.
[2] Adil Hameed, Alun Preece and Derek Sleeman. Ontology Reconciliation[EB]. prints. aktors. org/332/01 /p139.pdf, 2004.
[3] Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini. A Framework for Ontology Integration[A]. In: Proceedings of the 2001 Int. Semantic Web Working Symposium (SWWS 2001): 303-316.
[4] H.Sofia Pinto, et al. Some issues on Ontology Integration[A]. In proceedings of the IJCAI-99workshop Ontologies and Problem-solving methods (KRR5), Stockholm, Sweden, August, 1999.
[5] M. Ehrig and Y. Sure. Ontology mapping - an integrated approach. In Proceedings of the European Semantic Web Symposium (ESWS), pages 76-91, 2004.
[6] H. H. Do and E. Rahm. COMA - a system for flexible combination of schema matching approaches. In Proceedings of the Very Large Data Bases Conference (VLDB), pages 610-621, 2001.
[7] A. Doan, J. Madhavan, P. Domingos, and A. Halevy. Learning to map ontologies on the semantic web. In Proceedings of the International World Wide Web Conference, pages 662-673,2003.
[8] F. Giunchiglia, P. Shvaiko, and M. Yatskevich. Semantic schema matching. Technical Report DIT-05-014, University of Trento, 2005.
[9] A. Maedche, B. Motik, N. Silva, R. Volz.MAFRA - A Mapping Framework for Distributed Ontologies. In 13th European Conference on knowledge Engineering and ang knowledge Management, Spain, 2002.
[10] Fowler J, Nodine M, Perry B, et al. Agent - based semantic interoperability in Infosleuth[Z]. Sigmod Record, 1999.
[11] Thomas R. Gruber: "A Translation Approach to Portable Ontology Specifications" ; Knowledge Acquisition, Vol.5 No.2, pp.199-220, 1993.
[12] B. Ganter, R. Wille. Formal Concept Analysis: Mathematical Foundations. Springer, Berlin-Heidelberg - New York, 1999.
[13]M. H. Burnstein, Dynamic invocation of Semantic Web Services that use unfamiliar ontologies. IEEE Intell. Syst, 2004, 19(4): 67-73.
[14] S. Castano, et al. From Surface to Intensive Matching of Semantic Web Ontologies[A]. In: Proceedings of the 15th International Workshop on Database and Expert Systems Applications (DEXA'04), 2004: 140-144.
[15]Euzenat,J.,Valtech,P.Similarity-Based Ontology Alignment in OWL-Lite[A].In:Proceedings of the 15th ECAI,Valencia(ES),2004:333-337.
[16]简宁胜.一个本体映射工具的设计与实现.硕士学位论文,东南大学,2006.
[17]唐杰,梁邦勇,李涓子,王克宏.语义web中的本体自动映射.计算机学报,2006.
[18]Chang C C K,Garcia-Molina H.Conjunctive Constraint Mapping for Data Translation.In:Third ACM Conference on Digital Libraries,Pittsburgh,Pa.June 1998.49-58.
[19]Chawathe S,Garcia-Molina H,Hammer J,Ireland K,Papakonstantinou Y,Ulhnan J,Widom J.The TSIMMIS Project:Integration of Heterogeneous Information Sources.In:16th Meeting of the Information Processing Society of Japan(I PSP94),Tokyo,Japan,1994.7-18.
[20]Guha R V.Contexts:a Formalization and Some Applications.PhD.Thesis.Stanford University,1991.Also publishedas Technical Report STAN-CS-91-1399-Thesis,and MCC Technical Report Number ACT-CYC-423-91.
[21]Weinstein P C,Birmingham P.Creating Ontological Metadata for Digital Library Content and Services.International Journal on Digital Libraries,1998,2(1):19-36.
[22]Farquhar A,Fikes R,Rice J.The Ontolingua server:A tool for collaborative ontology construction.Int'l Journal of Human-Computer Studies,1997,46(6):707-727.
[23]Neches R,Fikes R E,Gruber T R,et al.Enabling Technology for Knowledge Sharing.AIMagazine,1991,12(3):36-56.
[24]Duineveld A J,Stoter R,Weiden MR,Kenepa B,Benjamins VR.Wonder tools.A comparative study of ontological engineering tools.Int'l Journal of Human-Computer Studies,2000,52(6):1111-1133.
[25]http://gis.pku.edu.cn/Resources/TR/Ontology_study _application.doc,2003.
[26]He Yanli,Yang Haicheng,He Weiping et al.Knowledge Integration for Information Integration [J].Computer Engineering and Applications,2003(4):38-41.
[27]Bozsak E,Ehrig M,Handschuh S,Hotho A,Maedche A,Motik B,Oberle D,Schmitz C,Staab S,Stojanovic L,Stojanovic N,Studer R,Stumme G,Sure Y,Tane J,Volz R,Zacharias V.KAON-Towards a large scale semantic web.In:Bauknecht K,Mintjoa A,Quirchmayr G,eds.Proc.of the 3rd Int'l Conf.on E-Commerce and Web Technologies.Heidelberg:Springer-Verlag,2002.304-313.
[28]http://www.cs.umd.edu/projects/plus/SHOE/.
[29]http://www.ai.sri.com/pkarp/xol/.
[30]http://www.w3.org/TR/rdf-primer.2004.02.10.
[31]Dan Brickley,Guha R V.Resource description framework(RDF) schema specification 1.0.[EB/OL].http://www.w3.org/TR/rdf-schema.
[32]Ian Horrocks.DAML+OIL:a description logic for the semantic web[C].Bull.of the IEEE Computer Society Technical Committee on Data Engineering,25(1):4-9,March 2002.
[33]Dean M,Schreiber G.OWL web ontology language reference[EB/OL],http://www.w3c.rg/TR/owl-ref,2004-02-10.
[34]Sheila A.McIlraith,Tran Cao Son,and Honglei Zeng.Semantic Web Services[J].IEEE Intelligent Systems,Special Issue on the Semantic Web,2001,16(2):46-53.
[35]T.Berners-Lee,J.Hendler,O.Lassila.The Semantic Web.Scientific American,2001(5):29-37.
[36]Yannis Kalfoglou,Harith Alani,Marco Schorlemmer,and ChrisWalton.On the Emergent Semantic Web and Overlooked Issues[A].In:Proceedings of ISWC 2004,LNCS 3298:576-590.
[37]T.Berners Lee RDF and the Semantic Web.Technical Report,XML 2000 Confemce in Washington,D.C.,USA,2000.
[38]Web Services Architecture,W3C Working Draft 14 November,2002.
[39]SWWS-Semantic Web Enabled Web Services[R].swws.semanticweb.org/public_doc/D2.2.pdf [Version:1.0 Date:23/09/2004].
[40]Jiehan Zhou,Juha-Pekka Koivisto,Eila Niemela.A Survey on Semantic Web Services and a Case Study[A].In:Proceedings of the 10th International Conference on CSCW in Design.2006,763-769.
[41]http://www.daml.org/services/owl-s/.Last Updated-$Date:2004/0/TR>.
[42]D.Roman,H.Lausen,U.Keller ed.Web Service Modeling Ontology(WSMO).Deliverable D2[R].version 1.2,2005.http://www.wsmo.org/TR/d2/.
[43]Martin Hepp.Semantic Web and Semantic Web Services[J].IEEE Internet Computing.2006(2),85-88.
[44]Gomadam.Radiant:A tool for semantic annotation of Web Services[A].In Proceedings of ISWC2005.
[45]Fensel D.,Horrocks L.,van Harmelen F.,Decker S.,Erdmann M.,Klein M..OIL in a nutshell.Proceedings of EKAW2000,LNAI,Springer,2000:1-16.
[46]E.Rahm,P.Bernstein.A survey of approaches to automatic schema matching.The International Journal on Very Large Data Bases(VLDB),2001,10(4):334-350.
[47]Noy N,Musen M.PROMPT:algorithm and tool for automated ontology merging and alignment.In Proceedings of AAAI,2000.AAAI Press,2000.
[48]Noy N,Musen M.SMART:automated support for ontology merging and alignment.In Proceedings of 12 th Workshop on Knowledge Acquisition,Moeling,and Management,Banff,Canada,1999.
[49]Dou D,McDermott D,Qi P.Ontology translation by ontology merging and automated reasoning.Ph thesis.University of Yale,2004.
[50]黄烟波,张红宇,李建华等.本体映射方法研究[J].计算机工程与应用.2005(18):27-29,33.
[51]Ehrig M,Staab S.QOM-Quick Ontology Mapping[C]//In:ISWC 2004,LNCS 3298.[s.l.]:[s.n.],2004:683-697.
[52]P.R.S.Visser, Z. Cui. On Accepting Heterogeneous Ontologies in Distributed Architectures. In Proceedings of the ECAI98 Workshop on Applications of Ontologies and Problem_Solving Methods. Brighton, UK, 1998.
[53] Yigal Arens, Chun-Non Hsu, and Craig A. Knoblock. Query processing in the sims information mediator. In Advanced Planning Technology. AAAI Press, California, USA, 1996.
[54]Satoshi Sekine, Kiyoshi Sudo, Takano Ogino. Statistical Matching of Two Ontologies. In: Proceedings of the SIGLEX99: Standerdizing Lexical Resources, University of Maryland, USA, 1999:69-73.
[55] A.Rodriguez, M.Egenhofer. Determining Semantic Similarity Among Entity Classes from Different Ontologies. IEEE Transactions on Knowledge and Data Engineering, 2003, 15(2):442-456.
[56] M Ehrig, Y Sure. Ontology Mapping- An Integrated Approach[C].In: Proceedings of the 1st European Semantic Web Symposium, Heraklion, Greece, Springer, LNCS, 2004-05:10-12.
[57] Sushama Prasad. A Tool for Mapping between Two Ontologies Using Explicit Information. In: Proceedings, AAMAS 2002 Workshop on Ontologies and Agent Systems, July 2002.
[58]Noy, N.F., Musen, M.A.: Anchor-Prompt: Using Non-local Context for Semantic Matching. In Proceedings of the Workshop on Ontologies and Information Sharing, 2003, 15(2):442-456.
[59] Chimaera. http://www.ksl.stanford.edu/software/chimaera/.
[60] Anhai Doan 数据网站. http://anhai.cs.uiuc.edu/archive/summary.type.html.
[61] George A. Miller. WordNet: A Lexical Database for English [J] . Communications of the ACM 38(11) (1995) 39-41.
[62]Fausto Giunchiglia, Pavel Shvaiko, Mikalai Yatskevich. S-Match: An Algorithm and an Implementation of Semantic Matching [J] . In Proceedings of ESWC (2004) 61-75.
[63] Bach Thanh Le, Rose Dieng-Kuntz, Fabien Gandon. On Ontology Matching Problems for Building a Corporate Semantic Web in a Multi-Communities Organization [J] . In Proceedings of the 6th International Conference on Enterprise Information Systems (2004) 236-243.
[64] Sergey Melnik, Hector Garcia-Molina, Erhard Rahm. Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching [J] . In Proceedings of the 18th International Conference on Data Engineering (2002) 117-128.
[65] Jayant Madhavan, Philip A. Bernstein, Erhard Rahm. Generic schema matching with Cupid[J]. In Proceedings of VLDB (2001) 49-58.
[66]Noy N.F., Musen M.A. PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment. In: Proceedings of the 17th National Conference on Artificial Intelligence (AAAI-2000), Austin, TX, 2000:450-455.
[67]Jérome Euzenat, Petko Valtchev. Similarity-based ontology alignment in OWL-Lite [J] . In Proceedings of ECAI (2004) 333-337.
[68]Bayardo R, Bohrer W, Brice R, et al. Infosleuth: Agent-based Semantic Integration of Information in open and Dynamic Environments[C]. Preceedings of the ACM International Conference on the Management of Data, 1997-05.
[69]Mena E, Illarramendi A, Kashyap V, Sheth A P. OBSERVER: An Approach for Query Processing in Global Information Systems Based on Interoperation Across Preexisting Ontologies. In: Proceedings of the First IFCIS International Conference on Cooperative Information Systems (CoopIS'96). Brussels, Belgium, 1996.19-21.
[70]T. G. Dietterich. Machine learning research: Four current directions. AI Magazine, 1997, 18(4): 97-136.
[71] Y Yang, X Lin. A re-examination of text categorization methods[C]. The 22nd Annual Int'l ACM SIGIR Conf on Research and Development in the Information Retrieval, Berkeley, California, USA, 1999.
[72] D D Lewis. Naive (Bayes) at forty: The independence assumption in information retrieval[C]. The 10th European Conf on Machine Learning, Heidelberg, Germany, 1998.
[2] Adil Hameed, Alun Preece and Derek Sleeman. Ontology Reconciliation[EB]. prints. aktors. org/332/01 /p139.pdf, 2004.
[3] Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini. A Framework for Ontology Integration[A]. In: Proceedings of the 2001 Int. Semantic Web Working Symposium (SWWS 2001): 303-316.
[4] H.Sofia Pinto, et al. Some issues on Ontology Integration[A]. In proceedings of the IJCAI-99workshop Ontologies and Problem-solving methods (KRR5), Stockholm, Sweden, August, 1999.
[5] M. Ehrig and Y. Sure. Ontology mapping - an integrated approach. In Proceedings of the European Semantic Web Symposium (ESWS), pages 76-91, 2004.
[6] H. H. Do and E. Rahm. COMA - a system for flexible combination of schema matching approaches. In Proceedings of the Very Large Data Bases Conference (VLDB), pages 610-621, 2001.
[7] A. Doan, J. Madhavan, P. Domingos, and A. Halevy. Learning to map ontologies on the semantic web. In Proceedings of the International World Wide Web Conference, pages 662-673,2003.
[8] F. Giunchiglia, P. Shvaiko, and M. Yatskevich. Semantic schema matching. Technical Report DIT-05-014, University of Trento, 2005.
[9] A. Maedche, B. Motik, N. Silva, R. Volz.MAFRA - A Mapping Framework for Distributed Ontologies. In 13th European Conference on knowledge Engineering and ang knowledge Management, Spain, 2002.
[10] Fowler J, Nodine M, Perry B, et al. Agent - based semantic interoperability in Infosleuth[Z]. Sigmod Record, 1999.
[11] Thomas R. Gruber: "A Translation Approach to Portable Ontology Specifications" ; Knowledge Acquisition, Vol.5 No.2, pp.199-220, 1993.
[12] B. Ganter, R. Wille. Formal Concept Analysis: Mathematical Foundations. Springer, Berlin-Heidelberg - New York, 1999.
[13]M. H. Burnstein, Dynamic invocation of Semantic Web Services that use unfamiliar ontologies. IEEE Intell. Syst, 2004, 19(4): 67-73.
[14] S. Castano, et al. From Surface to Intensive Matching of Semantic Web Ontologies[A]. In: Proceedings of the 15th International Workshop on Database and Expert Systems Applications (DEXA'04), 2004: 140-144.
[15]Euzenat,J.,Valtech,P.Similarity-Based Ontology Alignment in OWL-Lite[A].In:Proceedings of the 15th ECAI,Valencia(ES),2004:333-337.
[16]简宁胜.一个本体映射工具的设计与实现.硕士学位论文,东南大学,2006.
[17]唐杰,梁邦勇,李涓子,王克宏.语义web中的本体自动映射.计算机学报,2006.
[18]Chang C C K,Garcia-Molina H.Conjunctive Constraint Mapping for Data Translation.In:Third ACM Conference on Digital Libraries,Pittsburgh,Pa.June 1998.49-58.
[19]Chawathe S,Garcia-Molina H,Hammer J,Ireland K,Papakonstantinou Y,Ulhnan J,Widom J.The TSIMMIS Project:Integration of Heterogeneous Information Sources.In:16th Meeting of the Information Processing Society of Japan(I PSP94),Tokyo,Japan,1994.7-18.
[20]Guha R V.Contexts:a Formalization and Some Applications.PhD.Thesis.Stanford University,1991.Also publishedas Technical Report STAN-CS-91-1399-Thesis,and MCC Technical Report Number ACT-CYC-423-91.
[21]Weinstein P C,Birmingham P.Creating Ontological Metadata for Digital Library Content and Services.International Journal on Digital Libraries,1998,2(1):19-36.
[22]Farquhar A,Fikes R,Rice J.The Ontolingua server:A tool for collaborative ontology construction.Int'l Journal of Human-Computer Studies,1997,46(6):707-727.
[23]Neches R,Fikes R E,Gruber T R,et al.Enabling Technology for Knowledge Sharing.AIMagazine,1991,12(3):36-56.
[24]Duineveld A J,Stoter R,Weiden MR,Kenepa B,Benjamins VR.Wonder tools.A comparative study of ontological engineering tools.Int'l Journal of Human-Computer Studies,2000,52(6):1111-1133.
[25]http://gis.pku.edu.cn/Resources/TR/Ontology_study _application.doc,2003.
[26]He Yanli,Yang Haicheng,He Weiping et al.Knowledge Integration for Information Integration [J].Computer Engineering and Applications,2003(4):38-41.
[27]Bozsak E,Ehrig M,Handschuh S,Hotho A,Maedche A,Motik B,Oberle D,Schmitz C,Staab S,Stojanovic L,Stojanovic N,Studer R,Stumme G,Sure Y,Tane J,Volz R,Zacharias V.KAON-Towards a large scale semantic web.In:Bauknecht K,Mintjoa A,Quirchmayr G,eds.Proc.of the 3rd Int'l Conf.on E-Commerce and Web Technologies.Heidelberg:Springer-Verlag,2002.304-313.
[28]http://www.cs.umd.edu/projects/plus/SHOE/.
[29]http://www.ai.sri.com/pkarp/xol/.
[30]http://www.w3.org/TR/rdf-primer.2004.02.10.
[31]Dan Brickley,Guha R V.Resource description framework(RDF) schema specification 1.0.[EB/OL].http://www.w3.org/TR/rdf-schema.
[32]Ian Horrocks.DAML+OIL:a description logic for the semantic web[C].Bull.of the IEEE Computer Society Technical Committee on Data Engineering,25(1):4-9,March 2002.
[33]Dean M,Schreiber G.OWL web ontology language reference[EB/OL],http://www.w3c.rg/TR/owl-ref,2004-02-10.
[34]Sheila A.McIlraith,Tran Cao Son,and Honglei Zeng.Semantic Web Services[J].IEEE Intelligent Systems,Special Issue on the Semantic Web,2001,16(2):46-53.
[35]T.Berners-Lee,J.Hendler,O.Lassila.The Semantic Web.Scientific American,2001(5):29-37.
[36]Yannis Kalfoglou,Harith Alani,Marco Schorlemmer,and ChrisWalton.On the Emergent Semantic Web and Overlooked Issues[A].In:Proceedings of ISWC 2004,LNCS 3298:576-590.
[37]T.Berners Lee RDF and the Semantic Web.Technical Report,XML 2000 Confemce in Washington,D.C.,USA,2000.
[38]Web Services Architecture,W3C Working Draft 14 November,2002.
[39]SWWS-Semantic Web Enabled Web Services[R].swws.semanticweb.org/public_doc/D2.2.pdf [Version:1.0 Date:23/09/2004].
[40]Jiehan Zhou,Juha-Pekka Koivisto,Eila Niemela.A Survey on Semantic Web Services and a Case Study[A].In:Proceedings of the 10th International Conference on CSCW in Design.2006,763-769.
[41]http://www.daml.org/services/owl-s/.Last Updated-$Date:2004/0/TR>.
[42]D.Roman,H.Lausen,U.Keller ed.Web Service Modeling Ontology(WSMO).Deliverable D2[R].version 1.2,2005.http://www.wsmo.org/TR/d2/.
[43]Martin Hepp.Semantic Web and Semantic Web Services[J].IEEE Internet Computing.2006(2),85-88.
[44]Gomadam.Radiant:A tool for semantic annotation of Web Services[A].In Proceedings of ISWC2005.
[45]Fensel D.,Horrocks L.,van Harmelen F.,Decker S.,Erdmann M.,Klein M..OIL in a nutshell.Proceedings of EKAW2000,LNAI,Springer,2000:1-16.
[46]E.Rahm,P.Bernstein.A survey of approaches to automatic schema matching.The International Journal on Very Large Data Bases(VLDB),2001,10(4):334-350.
[47]Noy N,Musen M.PROMPT:algorithm and tool for automated ontology merging and alignment.In Proceedings of AAAI,2000.AAAI Press,2000.
[48]Noy N,Musen M.SMART:automated support for ontology merging and alignment.In Proceedings of 12 th Workshop on Knowledge Acquisition,Moeling,and Management,Banff,Canada,1999.
[49]Dou D,McDermott D,Qi P.Ontology translation by ontology merging and automated reasoning.Ph thesis.University of Yale,2004.
[50]黄烟波,张红宇,李建华等.本体映射方法研究[J].计算机工程与应用.2005(18):27-29,33.
[51]Ehrig M,Staab S.QOM-Quick Ontology Mapping[C]//In:ISWC 2004,LNCS 3298.[s.l.]:[s.n.],2004:683-697.
[52]P.R.S.Visser, Z. Cui. On Accepting Heterogeneous Ontologies in Distributed Architectures. In Proceedings of the ECAI98 Workshop on Applications of Ontologies and Problem_Solving Methods. Brighton, UK, 1998.
[53] Yigal Arens, Chun-Non Hsu, and Craig A. Knoblock. Query processing in the sims information mediator. In Advanced Planning Technology. AAAI Press, California, USA, 1996.
[54]Satoshi Sekine, Kiyoshi Sudo, Takano Ogino. Statistical Matching of Two Ontologies. In: Proceedings of the SIGLEX99: Standerdizing Lexical Resources, University of Maryland, USA, 1999:69-73.
[55] A.Rodriguez, M.Egenhofer. Determining Semantic Similarity Among Entity Classes from Different Ontologies. IEEE Transactions on Knowledge and Data Engineering, 2003, 15(2):442-456.
[56] M Ehrig, Y Sure. Ontology Mapping- An Integrated Approach[C].In: Proceedings of the 1st European Semantic Web Symposium, Heraklion, Greece, Springer, LNCS, 2004-05:10-12.
[57] Sushama Prasad. A Tool for Mapping between Two Ontologies Using Explicit Information. In: Proceedings, AAMAS 2002 Workshop on Ontologies and Agent Systems, July 2002.
[58]Noy, N.F., Musen, M.A.: Anchor-Prompt: Using Non-local Context for Semantic Matching. In Proceedings of the Workshop on Ontologies and Information Sharing, 2003, 15(2):442-456.
[59] Chimaera. http://www.ksl.stanford.edu/software/chimaera/.
[60] Anhai Doan 数据网站. http://anhai.cs.uiuc.edu/archive/summary.type.html.
[61] George A. Miller. WordNet: A Lexical Database for English [J] . Communications of the ACM 38(11) (1995) 39-41.
[62]Fausto Giunchiglia, Pavel Shvaiko, Mikalai Yatskevich. S-Match: An Algorithm and an Implementation of Semantic Matching [J] . In Proceedings of ESWC (2004) 61-75.
[63] Bach Thanh Le, Rose Dieng-Kuntz, Fabien Gandon. On Ontology Matching Problems for Building a Corporate Semantic Web in a Multi-Communities Organization [J] . In Proceedings of the 6th International Conference on Enterprise Information Systems (2004) 236-243.
[64] Sergey Melnik, Hector Garcia-Molina, Erhard Rahm. Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching [J] . In Proceedings of the 18th International Conference on Data Engineering (2002) 117-128.
[65] Jayant Madhavan, Philip A. Bernstein, Erhard Rahm. Generic schema matching with Cupid[J]. In Proceedings of VLDB (2001) 49-58.
[66]Noy N.F., Musen M.A. PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment. In: Proceedings of the 17th National Conference on Artificial Intelligence (AAAI-2000), Austin, TX, 2000:450-455.
[67]Jérome Euzenat, Petko Valtchev. Similarity-based ontology alignment in OWL-Lite [J] . In Proceedings of ECAI (2004) 333-337.
[68]Bayardo R, Bohrer W, Brice R, et al. Infosleuth: Agent-based Semantic Integration of Information in open and Dynamic Environments[C]. Preceedings of the ACM International Conference on the Management of Data, 1997-05.
[69]Mena E, Illarramendi A, Kashyap V, Sheth A P. OBSERVER: An Approach for Query Processing in Global Information Systems Based on Interoperation Across Preexisting Ontologies. In: Proceedings of the First IFCIS International Conference on Cooperative Information Systems (CoopIS'96). Brussels, Belgium, 1996.19-21.
[70]T. G. Dietterich. Machine learning research: Four current directions. AI Magazine, 1997, 18(4): 97-136.
[71] Y Yang, X Lin. A re-examination of text categorization methods[C]. The 22nd Annual Int'l ACM SIGIR Conf on Research and Development in the Information Retrieval, Berkeley, California, USA, 1999.
[72] D D Lewis. Naive (Bayes) at forty: The independence assumption in information retrieval[C]. The 10th European Conf on Machine Learning, Heidelberg, Germany, 1998.