Journal of Computer Applications     2012 32 (04):  1094-1096    ISSN: 1001-9081:  CN: 51-1307/TP Ontology similarity computation using k-partite ranking method LAN Mei-hui 1,REN You-jun 1,XU Jian 1,GAO Wei 2, 3 1. College of Computer Science and Engineering, Qujing Normal University, Qujing Yunnan 655011, China 2. College of Information, Yunnan Normal University , Kunming Yunan 650092, China 3. College of mathematical Sciences, Soochow University, Suzhou Jiangsu 215006, China Received 2011-10-31  Revised 2011-12-06  Online 2012-04-01 Reference  ［1］ MORK P, BERNSTEIN P. Adapting a generic match algorithm to align ontologies of human anatomy［C］// Proceedings of 20th International Conference on Data Engineering. Los Alamitos: IEEE Computer Society, 2004: 787-790. ［2］ LAMBRIX P, EDBERG A. Evaluation of ontology merging tools in bioinformatics［EB/OL］.[2011-06-10].http://helix-web.stanford.edu/psb03/lambrix.pdf. ［3］ BOUZEGHOUB A, ELBYED A. Ontology mapping for Web-based educational systems interoperability［J］.Interoperability in Business Information Systems,2006, 1(1): 73-84. ［4］ WANG Y, GAO W, ZHANG Y, et al.Ontology similarity computation use ranking learning method ［C］// 3rd International Conference on Computational Intelligence and Industrial Application. Washington, DC: IEEE Computer Society, 2010: 20-23. ［5］ WANG Y, GAO W, ZHANG Y, et al.Push ranking learning algorithm on graphs ［C］// International Conference on Circuit and Signal Processing. Washington, DC: IEEE Computer Society, 2010 : 368-371. ［6］ LAN M, XU J, GAO W. Ontology similarity measure based on preference graphs ［C］// International Conference on E-business and Information System Security. Washington, DC: IEEE Computer Society, 2011: 667-670. ［7］ LAN M, XU J, GAO W. Ontology mapping algorithm based on primal RankRLS ［C］// International Conference on E-business and Information System Security. Washington, DC: IEEE Computer Society, 2011: 788-790. ［8］ 兰美辉, 徐坚, 孙瑜. 基于谱图理论的本体相似度计算［J］. 计算机工程与应用, 2011, 47(28):110-112. ［9］ CYNTHIA R, ROBERT E, INGIRD D. Boosting based on a smooth margin［C］// Proceedings of the 16th Annual Conference on Computational Learning Theory. Berlin: Springer-verlag,2004: 502-517. ［10］ JOACHIMS T. Optimizing search engines using clickthrough data ［C］// Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM, 2002:133-142. ［11］ BURGES C. Learning to rank using gradient descent ［C］// Proceedings of the 22nd International Conference on Machine Learning. New York: ACM, 2005: 89-96. ［12］ CHUA T S, NEO S Y, GOH H K, et al.TRECVID 2005 by nus pris［C/OL］.[2011-10-01]. http://www-nlpir.nist.gov/projects/tvpubs/tv5.papers/nus.pdf. ［13］ CORINNA C, MEHRYAR M, ASHISH R. Magnitude-preserving ranking algorithms［C］// Proceedings of the 24th International Conference on Machine Learning. New York: ACM, 2007: 169-176. ［14］ DAVID C, TONG Z. Subset ranking using regression［C］// 19th Annual Conference on Learning Theory. Berlin: Springer-verlag. 2006: 605-619. ［15］ RONG Y, ALEXANDER, HAUPTMANN D. Efficient margin-based rank learning algorithms for information retrieval ［EB/OL］.[2011-06-20].http://www.informedia.cs.cmu.edu/documents/CIVR06_yan.pdf. ［16］ CYNTHIA R. Ranking with a p-norm push［C］// 19th Annual Conference on Learning Theory. Berlin: Springer-verlag,2006: 589-604. ［17］ RAJARAM S, AGARWAL S. Generalization bounds for k-partite ranking［EB/OL］.[2011-06-25].http://drona.csa.iisc.ernet.in/～shivani/Publications/2005/nips05workshop.pdf. ［18］ the Gene Ontology [EB/OL].[2011-08-01]. http://www.geneontology.org. ［19］ CRASWELL N, HAWKING D. Overview of the TREC 2003 Web track［EB/OL］.[2011-06-01].http://david-hawking.net/pubs/overview_trecweb2003.pdf. Corresponding author: LAN Mei-hui