[1] Ji Qiu, Qi Guilin, Boutouhami Khaoula, et al. Revision of stratified OWL ontologiesbased on integer linear programming [J]. Journal of Southeast University (English Edition), 2020, 36 (1): 1-7. [doi:10.3969/j.issn.1003-7985.2020.01.001]

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

36

Issue:

2020 1

Page:

1-7

Research Field:

Automation

Publishing date:

2020-03-20

Info

Title:

Revision of stratified OWL ontologiesbased on integer linear programming

Author(s):

Ji Qiu¹;  Qi Guilin²;  3;  Boutouhami Khaoula²;  3

¹School of Modern Posts, Nanjing University of Posts and Telecommunications, Nanjing 210023, China
²School of Computer Science and Engineering, Southeast University, Nanjing 211189, China
³Key Laboratory of Computer Network and Information Integration of Ministry of Education, Southeast University, Nanjing 211189, China

Keywords:

ontology revision;  inconsistency handling;  semantic web;  integer linear programming

PACS:

TP181

DOI:

10.3969/j.issn.1003-7985.2020.01.001

Abstract:

To revise stratified web ontology language(OWL)ontologies, the kernel revision operator is extended by defining novel conflict stratification and the incision function based on integer linear programming(ILP). The ILP-based model considers an optimization problem of minimizing a linear objective function which is suitable for selecting the minimal number of axioms to remove when revising ontologies. Based on the incision function, a revision algorithm is proposed to apply ILP to all minimal incoherence-preserving subsets(MIPS). Although this algorithm can often find a minimal number of axioms to remove, it is very time-consuming to compute MIPS. Thus, an adapted revision algorithm to deal with unsatisfiable concepts individually is also given. Experimental results reveal that the proposed ILP-based revision algorithm is much more efficient than the commonly used algorithm based on the hitting set tree. In addition, the adapted algorithm can achieve higher efficiency, while it may delete more axioms.

References:

[1] Grau C B, Horrocks I, Motik B, et al. OWL 2: The next step for OWL[J]. Journal of Web Semantics, 2008, 6(4): 309-322. DOI: 10.1016/j.websem.2008.05.001.
[2] Ji Q, Qi G L, Gao H, et al. Survey on schema induction from knowledge graphs [C]//China Conference of Knowledge Graph and Semantic Computing. Tianjin, China, 2018:136-142.
[3] Zablith F, Antoniou G, d’Aquin M, et al. Ontology evolution: A process-centric survey[J]. The Knowledge Engineering Review, 2015, 30(1): 45-75. DOI:10.1017/s0269888913000349.
[4] Qi G L, Haase P, Huang Z S, et al. A kernel revision operator for terminologies—algorithms and evaluation [C]// 7th International Semantic Web Conference. Karlsruhe, Germany, 2008: 419-434.
[5] Ribeiro M M, Wassermann R, Flouris G, et al. Minimal change: Relevance and recovery revisited[J]. Artificial Intelligence, 2013, 201: 59-80. DOI:10.1016/j.artint.2013.06.001.
[6] Golbeck J, Halaschek-Wiener C. Trust-based revision for expressive web syndication[J]. Journal of Logic and Computation, 2009, 19(5): 771-790. DOI:10.1093/logcom/exn045.
[7] Zhuang Z Q, Wang Z, Wang K W, et al. DL-Lite contraction and revision[J]. Journal of Artificial Intelligence Research, 2016, 56: 329-378. DOI:10.1613/jair.5050.
[8] Fu X F, Qi G L, Zhang Y, et al. Graph-based approa-ches to debugging and revision of terminologies in DL-Lite[J]. Knowledge-Based Systems, 2016, 100: 1-12. DOI:10.1016/j.knosys.2016.01.039.
[9] Qi G L, Du J F. Model-based revision operators for terminologies in description logics [C]// 21st International Joint Conference on Artificial Intelligence. Pasadena, CA, USA, 2009: 891-897.
[10] Wang Z, Wang K W, Zhuang Z Q, et al. Instance-driven ontology evolution in DL-Lite [C]// 29th AAAI Conference on Artificial Intelligence. Austin, TX, USA, 2015: 1656-1662.
[11] Micalizio R, Pozzato G L. Revision of ontologies to accommodate exceptions: A typicality-based approach[J]. Fundamenta Informaticae, 2018, 161(1/2): 163-189. DOI:10.3233/fi-2018-1699.
[12] Ji Q, Gao Z Q, Huang Z S. Conflict resolution in partially ordered OWL DL ontologies [C]// 21st European Conference on Artificial Intelligence. Prague, Czech Republic, 2014: 471-476.
[13] Dong X L, Gabrilovich E, Heitz G, et al. From data fusion to knowledge fusion[J]. Proceedings of the VLDB Endowment, 2014, 7(10): 881-892. DOI:10.14778/2732951.2732962.
[14] Bobillo F, Straccia U. Reducing the size of the optimization problems in fuzzy ontology reasoning [C]//11th International Workshop on Uncertainty Reasoning for the Semantic Web. Bethlehem, USA, 2015: 54-59.
[15] Niepert M, Meilicke C, Stuckenschmidt H. A probabilistic-logical framework for ontology matching [C]// 24th AAAI Conference on Artificial Intelligence. Atlanta, GA, USA, 2010: 1413-1418.
[16] Wang Q, Wang B, Guo L, et al. Knowledge base completion using embeddings and rules [C]// 24th International Joint Conference on Artificial Intelligence. Buenos Aires, Argentina, 2015: 1859-1866.
[17] Ji Q, Boutouhami K, Qi G L. Resolving logical contradictions in description logic ontologies based on integer linear programming[J]. IEEE Access, 2019, 7: 71500-71510. DOI:10.1109/access.2019.2919498.
[18] Baader F, Calvanese D, McGuinness D L, et al. The description logic handbook[M]. Cambridge: Cambridge University Press, 2007. DOI:10.1017/cbo9780511711787.
[19] Li H Y, Shao C P, Wang Z. Detecting fault injection attacks based on compressed sensing and integer linear programming[J]. IEEE Transactions on Dependable and Secure Computing, 2019, 16(3): 476-483. DOI:10.1109/tdsc.2018.2821140.
[20] Karp R M. Reducibility among combinatorial problems [C]// A symposium on the Complexity of Computer Computations. Yorktown Heights, NY, USA, 1972: 85-103.
[21] Baader F, Penaloza R, Suntisrivaraporn B. Pinpointing in the description logic EL+ [C]// 30th Annual German Conference on AI. Osnabrück, Germany, 2007: 52-67.
[22] Ji Q, Qi G L, Haase P. A relevance-directed algorithm for findingjustifications of DL entailments [C]// 4th Annual Asian Semantic Web Conference. Shanghai, China, 2009: 306-320.

Memo

Memo:

Biography: Ji Qiu(1980—), female, doctor, lecturer, qiuji@njupt.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.61602259, U1736204), Research Foundation for Advanced Talents of Nanjing University of Posts and Telecommunications(No.NY216022), the National Key Research and Development Program of China(No.2018YFC0830200).
Citation: Ji Qiu, Qi Guilin, Boutouhami Khaoula. Revision of stratified OWL ontologies based on integer linear programming[J].Journal of Southeast University(English Edition), 2020, 36(1):1-7.DOI:10.3969/j.issn.1003-7985.2020.01.001.

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