吉林大学学报(工学版) ›› 2014, Vol. 44 ›› Issue (6): 1757-1763.doi: 10.13229/j.cnki.jdxbgxb201406034

Previous Articles     Next Articles

Local pinpointing of ontology debugging based on model-based diagnosis

OUYANG Dan-tong1, 2, SU Jing1, 2, YE Yu-xin1, 2, 3, CUI Xian-ji1, 2   

  1. 1.College of Computer Science and Technology, Jilin University, Changchun 130012,China;
    2.Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012,China;
    3.National Engineering Research Center of Geophysics Exploration Instruments, Jilin University, Changchun 130026, China
  • Received:2014-06-29 Online:2014-11-01 Published:2014-11-01

RICH HTML

0   

PDF (PC)

409

Abstract: We introduce the model-based diagnosis into local pinpointing of ontology debugging. The concept of MUCS is given on the basis of component terminology definition to achieve the local debugging on terminology. We take the advantage of MUCS to pinpoint the logical errors of unsatisfiable concept to the axiom interior, which is independent of the existing ontology debugging. One MUCS for an unsatisfiable concept is calculated by calling an external DL reasoner, and all MUCSs are obtained by combing the principal of breath-first with hitting set theory of Reiter. Finally, the realistic ontology is used to conduct a comprehensive test of the MUCS algorithm. Experimental results show that the MUCS debugging algorithm could point out the local position of logical conflict in an axiom specifically, and efficiently and accurately complete the ontology debugging task.

Key words: ontology debugging, pinpoint, mininal unsatisfiability preserving sub-TBox, mininal incoherence-preserving sub-TBoxes

CLC Number: 

  • TP181
[1] Meyer T, Lee Kevin, Booth R,et al. Finding maximally satisfiable terminologies for the description logic ALC[C]∥In: Proceedings of the 21st National Conference on Artificial Intelligence(AAAI-2006)Boston Massachusetts,2006,2:269-274.
[2] Schlobach S, Cornet R. Non-Standard reasoning services for the debugging of description logic terminologies[C]∥In: Proceedings of the International Joint Conference on Artificial Intelligence(IJCAI-03),Acapulco,Mexico,2003:355-360.
[3] Schlobach S, Huang Zhi-sheng, Cornet Ronald, et al. Debugging incoherent terminologies[J]. Journal of Automated Reasoning, 2007, 39(3): 317-349.
[4] Kalyanpur A, Parsia B, Sirin E, et al. Debugging unsatisfiable concepts in OWL ontologies[J]. Journal of Web Semantics, 2005, 3(4): 268-293.
[5] Kalyanpur A, Parsia B, Horridge M, et al. Finding all justifications of OWL DL entailments[J]. Lecture Notes in Computer Science, 2007, 4825: 267-280.
[6] Baader F, Pealoza R. Automata-based axiom pinpointing[C]∥In: Proceedings of 4th International Joint Conference on Automated Reasoning,Sydney,Australia,2008, 226-241.
[7] Schlobach S. Diagnosing terminologies[C]∥In: Proceedings of the 20th national conference on Artificial intelligence(AAAI-05),Pittsburgh,Pennsylvania,2005, 670-675.
[8] Reiter R. A theory of diagnosis from first principles[J]. Artificial Intelligence, 1987, 32(1): 57-95.
[9] 欧阳丹彤, 欧阳继红, 程晓春,等. 基于模型诊断中计算碰集的方法[J].仪器仪表学报,2004,25(4): 605-608. Ouyang Dan-tong, Ouyang Ji-hong, Cheng Xiao-chun,et al.A method of computing hitting set in model-based diagnosis[J]. Chinese Journal of Scientific Instrument,2004,25(4):605-608.
[10] Friedrich G, Shchekotykhin K. A general diagnosis method for ontologies[C]∥In: Proceedings of the 4th Iinternational Conference on The Semantic Web,Galway,Indand,2005:232-246.
[11] Shchekotykhin K, Friedrich G, Philipp F, et al. Interactive ontology debugging: two query strategies for efficient fault localization[J]. In Journal of Web Semantics, 2012, 12(13): 88-103.
[12] Haase P, Qi Gui-lin. An analysis of approaches to resolving inconsistencies in DL-based ontologies[C]∥In: Proceedings of the International Workshop on Ontology Dynamics (IWOD-07),Innsbruck,Austria,2007:97-109.
[1] GU Hai-jun, TIAN Ya-qian, CUI Ying. Intelligent interactive agent for home service [J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(5): 1578-1585.
[2] LI Xiong-fei, FENG Ting-ting, LUO Shi, ZHANG Xiao-li. Automatic music composition algorithm based on recurrent neural network [J]. 吉林大学学报(工学版), 2018, 48(3): 866-873.
[3] ZHANG Wei, LIU Yu-hui. Expressive power of decidable subclasses of open proxcheme [J]. 吉林大学学报(工学版), 2016, 46(6): 2021-2026.
[4] BAI Tian, JI Jin-chao, HE Jia-liang, ZHOU Chun-guang. New clustering method of mixed-attribute data [J]. 吉林大学学报(工学版), 2013, 43(01): 130-134.
[5] LIU Quan, YANG Xu-dong, JING Ling, XIAO Fei. Improved E3 algorithm based on multi-agent parallel sampling and learning experience reuse [J]. 吉林大学学报(工学版), 2013, 43(01): 135-140.
[6] TU Wei-wei, LI Ming, ZHOU Zhi-hua. Mining software defect factor [J]. 吉林大学学报(工学版), 2012, 42(增刊1): 382-386.
[7] ZHANG Ying-feng, MA Biao, ZHU Yuan, ZHANG Jin-le. State identification of power-shift steering transmission based on hypersphere support vector machine [J]. 吉林大学学报(工学版), 2012, 42(01): 13-18.
[8] KONG Ling-fu, LI Hai-tao. Elderly behavior analysis based on immune unsupervised classification [J]. 吉林大学学报(工学版), 2011, 41(6): 1699-1703.
[9] LIU Li, LIU Ping-ping, WEI Jia. Semi-supervised dimensionality reduction algorithm applying in face data with side information [J]. 吉林大学学报(工学版), 2011, 41(增刊1): 189-193.
[10] XU You-jun,OUYANG Dan-tong,YE Yu-xin,HE Jia-liang. Solving #SAT with extension rule indirectly [J]. 吉林大学学报(工学版), 2011, 41(4): 1047-1053.
[11] DONG Yuan-fang, LI Xiong-fei, LI Jun,LI Wei. IL-AdaBoost algorithm for XML document classification [J]. 吉林大学学报(工学版), 2011, 41(4): 1054-1058.
[12] YU Hua-long, GU Guo-chang, ZHAO Jing, LIU Hai-bo, SHEN Jing. Feature subspace ensemble classification based on DNA microarray data [J]. 吉林大学学报(工学版), 2011, 41(4): 1071-1076.
[13] ZHAN Yu-bin,YIN Jian-ping,LI Kuan. Learning manifold from incomplete image set [J]. 吉林大学学报(工学版), 2011, 41(03): 728-733.
[14] TIAN Ye, LIU Da-You. Improved clustering algorithm in peertopeer environments [J]. 吉林大学学报(工学版), 2010, 40(06): 1639-1643.
[15] LV Shuai, LIU Lei, JIANG Hong, WEI Wei. Classical optimal planning method based on compacted encodings [J]. 吉林大学学报(工学版), 2010, 40(06): 1644-1649.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright © Journal of Jilin University(Engineering and Technology Edition), All Rights Reserved.
Tel: +86-431-85095297　Fax: +86-431-85094074　E-mail: xbgxb@jlu.edu.cn
Powered by Beijing Magtech Co. Ltd