Fuzzy ontology alignment using background knowledge

International Journal of Uncertainty, Fuzziness and Knowldege-Based Systems

Volumn 22, Issue 1, 2014, Pages 75-112

  Todorov, Konstantin ^a   Hudelot, Celine ^b   Popescu, Adrian ^c   Geibel, Peter ^d  

^a LIRMM   (France)

^b Ecole Centrale de Paris   (France)

^c CEA LIST   (France)

^d CHARITÉ UNIVERSITÄTSMEDIZIN BERLIN   (Germany)

Author keywords

(fuzzy) ontology alignment; background knowledge; Fuzzy ontologies; information retrieval; wikipedia

Indexed keywords

INFORMATION RETRIEVAL;

(FUZZY) ONTOLOGY ALIGNMENT; BACKGROUND KNOWLEDGE; CORE FEATURES; DOMAIN CONCEPTS; FUZZY ONTOLOGY; MATCHING PROCESS; ONTOLOGY ALIGNMENT; WIKIPEDIA;

ONTOLOGY;

EID: 84900618295     PISSN: 02184885     EISSN: None     Source Type: Journal    
DOI: 10.1142/S0218488514500044     Document Type: Article

References (56)

1. J.-I. Akahani, K. Hiramatsu and T. Satoh, Approximate query reformulation based on hierarchical ontology mapping, in Proc. Int. Workshop SWFAT, 2003, pp. 43-46
2. Z. Aleksovski, M. Klein, W. Ten Kate and F. Van Harmelen, Matching unstructured vocabularies using a background ontology, Managing Knowledge in a World of Networks, 2006, pp. 182-197
3. Z. Aleksovski, W. ten Kate and F. van Harmelen, Exploiting the structure of background knowledge used in ontology matching, in Ontology Matching Workshop at Int. Semantic Web Conference (ISWC), 2006
4. A. Bahri, R. Bouaziz and F. Gargouri, Dealing with similarity relations in fuzzy ontologies, in IEEE Int. Fuzzy Systems Conf. 2007 (FUZZ-IEEE 2007), IEEE, 2007, pp. 1-6
5. F. Bobillo, Managing vagueness in ontologies, PhD thesis, University of Granada, Spain, 2008
6. P. Buche, J. Dibie-Barthélemy and L. Ibanescu, Ontology mapping using fuzzy conceptual graphs and rules, in ICCS Supplement, 2008, pp. 17-24
7. S. Calegari and D. Ciucci, Fuzzy ontology, fuzzy description logics and fuzzy-owl, in Applications of Fuzzy Sets Theory, eds. F. Masulli, S. Mitra and G. Pasi, LNCS, Vol. 4578 (Springer, Berlin/Heidelberg, 2007), pp. 118-126
8. S. Calegari and E. Sanchez, A fuzzy ontology-approach to improve semantic information retrieval, in Proc. Third ISWC Workshop on Uncertainty Reasoning for the Semantic Web-URSW, Vol. 7, 2007, p. 6
9. A. Cali and T. Lukasiewicz, Tightly integrated probabilistic description logic programs for the semantic web, in Proc. 23rd Int. Conf. Logic Programming (Springer-Verlag, 2007), pp. 428-429
10. V. Cross and X. Yu, A fuzzy set framework for ontological similarity measures, in WCCI 2010, FUZZ-IEEE 2010 (IEEE Compter Society Press, 2010), pp. 1-8
11. R. Diestel, Graph Theory, 4th edn., Graduate Texts in Mathematics, Vol. 173 (Springer, 2012
12. A. Doan, J. Madhavan, P. Domingos, and A. Halevy, Learning to map between ontologies on the semantic web, in WWW'02 (ACM Press, 2002), pp. 662-673
13. D. Dubois and H. Prade, Possibility theory, probability theory and multiple-valued logics: A clarification, Annals of Mathematics and Artificial Intelligence 32(1-4) (2001) 35-66
14. J. Euzenat and P. Shvaiko, Ontology Matching, 1st edn. (Springer-Verlag, 2007
15. N. Fanizzi, C. d'Amato, F. Esposito and T. Lukasiewicz, Representing uncertain concepts in rough description logics via contextual indiscernibility relations, in Proc. URSW, Vol. 8 (2008
16. U. Feige, S. Goldwasser, L. Lovasz, S. Safra and M. Szegedy, Approximating clique is almost NP-complete, in Annual IEEE Symposium on Foundations of Computer Science, Vol. 0, Los Alamitos, CA, USA (IEEE Computer Society, 1991), pp. 2-12
17. A. Ferrara, D. Lorusso, G. Stamou, G. Stoilos, V. Tzouvaras and T. Venetis, Resolution of conflicts among ontology mappings: A fuzzy approach, OM'08 at ISWC (2008
18. A. Gal, Managing uncertainty in schema matching with top-k schema mappings, Journal on Data Semantics VI, 2006, pp. 90-114
19. A. Gal and P. Shvaiko, Advances in web semantics I, Advances in Ontology Matching (Springer-Verlag, Berlin, Heidelberg, 2009), pp. 176-198
20. P. Geibel, K. Sch'adler and F. Wysotzki, Connectionist construction of prototypes from decision trees for graph classification, Intell. Data Anal. 7(2) (2003) 125-140
21. R. Gligorov, W. ten Kate, Z. Aleksovski and F. Van Harmelen, Using google distance to weight approximate ontology matches, in Proc. 16th Int. Conf. World Wide Web (ACM, 2007), pp. 767-776
22. T. R. Gruber, Towards Principles for the Design of Ontologies Used for Knowledge Sharing, in Formal Ontology in Conceptual Analysis and Knowledge Representation, eds. N. Guarino and R. Poli (Kluwer Academic Publishers, 1993
23. A. Y. Halevy, N. Ashish, D. Bitton, M. Carey, D. Draper, J. Pollock, A. Rosenthal and V. Sikka, Enterprise information integration: Successes, challenges and controversies, in Proc. 2005 ACM SIGMOD Int. Conf. Management of Data (SIGMOD '05) (ACM, 2005), pp. 778-787
24. T. Hofmann, Probabilistic latent semantic indexing, in Proc. 22nd Annual Int. ACM SIGIR Conf. Research and Development in Information Retrieval ( SIGIR '99), New York, USA (ACM, 1999), pp. 50-57
25. A. Isaac, L. van der Meij, S. Schlobach and S. Wang, An empirical study of instancebased ontology matching, The Semantic Web (2008), pp. 253-266
26. M. S. Lacher and G. Groh, Facilitating the exchange of explicit knowledge through ontology mappings, in Proc. 14th FLAIRS Conf. (AAAI Press, 2001), pp. 305-309
27. K. Lang, Newsweeder: Learning to filter netnews, in Proc. Twelfth Int. Conf. Machine Learning, 1995, pp. 331-339
28. J. Lee, A First Course in Combinatorial Optimization, Cambridge Texts in Applied Mathematics (Cambridge University Press, 2004
29. J. Madhavan, P. A. Bernstein and E. Rahm, Generic schema matching with cupid, in The VLDB Journal (2001), pp. 49-58
30. D. L. McGuinness, R. Fikes, J. Rice and S. Wilder, An environment for merging and testing large ontologies, in Proc. 17th Int. Conf. Principles of Knowledge Representation and Reasoning (KR'2000), Colorado, USA, April 2000, pp. 483-493
31. S. Melnik, H. Garcia-Molina and E. Rahm, Similarity flooding: A versatile graph matching algorithm and its application to schema matching, in Proc. 18th Int. Conf. Data Engineering (IEEE, 2002), pp. 117-128
32. G. A. Miller, WordNet: A lexical database for English, Commun. ACM 38(11) (1995) 39-41
33. M. Nagy, M. Vargas-Vera and E. Motta, Dssim-ontology mapping with uncertainty, in Ontology Matching Workshop at ISWC 2006, eds. P. Shvaiko, J. Euzenat, N. F. Noy, H. Stuckenschmidt, V. R. Benjamins and M. Uschold, CEUR Workshop Proc., Vol. 225, CEUR-WS.org, 2006
34. D. Ngo, Z. Bellahsene and K. Todorov, Opening the black box of ontology matching, in The Semantic Web: Semantics and Big Data (Springer, 2013), pp. 16-30
35. H. Nottelmann and U. Straccia, A probabilistic, logic-based framework for automated web directory alignment, Soft Computing in Ontologies and Semantic Web, 2006, pp. 47-77
36. N. Noy and M. Musen, Anchor-prompt: Using non-local context for semantic matching, in Workshop on Ontologies and Information Sharing at IJCAI, 2001, pp. 63-70
37. R. Pan, Z. Ding, Y. Yu and Y. Peng, A bayesian network approach to ontology mapping, The Semantic Web (ISWC 2005), 2005, pp. 563-577
38. C. Reynaud and B. Safar, Exploiting wordnet as background knowledge, in ISWC'07Ontology Matching (OM-07 Workshop 2007
39. C. Rosse, J. L. V. Mejino et al., A reference ontology for biomedical informatics: The foundational model of anatomy, Journal of Biomedical Informatics 36(6) (2003) 478-500
40. B. C. Russell, A. Torralba, K. P. Murphy and W. T. Freeman, Labelme: A database and web-based tool for image annotation, Int. J. Computer Vision 77(1) (2008
41. S. J. Russell and P. Norvig, Artificial Intelligence - A Modern Approach, 3rd edn. (Pearson Education, 2010
42. E. Sanchez and T. Yamanoi, Fuzzy ontologies for the semantic web, Flexible Query Answering Systems, 2006, pp. 691-699
43. P. Shvaiko and J. Euzenat, Ontology matching: State of the art and future challenges, IEEE TKDE, 99, 2011
44. A. W. M. Smeulders, M. Worring, S. Santini, A. Gupta and R. Jain, Content-based image retrieval at the end of the early years, IEEE Trans. Pattern Analysis and Machine Intelligence 22 (2000) 1349-1380
45. J. R. Smith and S. F. Chang, Large-scale concept ontology for multimedia, IEEE Multimedia 13(3) (2006) 86-91
46. U. Straccia, Towards a fuzzy description logic for the semantic web (preliminary report), in The Semantic Web: Research and Applications, eds. A. Gomez-Perez and J. Euzenat, Lecture Notes in Computer Science, Vol. 3532 (Springer, Berlin/Heidelberg, 2005), pp. 73-123
47. H. Stuckenschmidt, Approximate information filtering on the semantic web, in KI 2002, eds. M. Jarke, G. Lakemeyer and J. Koehler, LNCS, Vol. 2479 (Springer, Berlin/Heidelberg, 2002), pp. 195-228
48. G. Stumme and A. Maedche, FCA-merge: Bottom-up merging of ontologies, in IJCAI, 2001, pp. 225-230
49. K. Todorov, P. Geibel and C. Hudelot, Building a fuzzy knowledge body for integrating domain ontologies, in URSW, eds. F. Bobillo, R. N. Carvalho, P. da Costa, C. d'Amato, N. Fanizzi, K. B. Laskey, T. Lukasiewicz, T. Martin, and M. Nickles, CEUR Workshop Proc., Vol. 778, CEUR-WS.org, 2011, pp. 3-14
50. K. Todorov, P. Geibel and C. Hudelot, A framework for a fuzzy matching between multiple domain ontologies, in KES (1), eds. A. KÖnig, A. Dengel, K. Hinkelmann, K. Kise, R. J. Howlett, and L. C. Jain, Lecture Notes in Computer Science, Vol. 6881 (Springer, 2011), pp. 538-547
51. K. Todorov, P. Geibel and K.-U. Kühnberger, Mining concept similarities for heterogeneous ontologies, in Advances in Data Mining. Applications and Theoretical Aspects, ed. P. Perner, LNCS, Vol. 6171 (Springer, Berlin/Heidelberg, 2010), pp. 86-100
52. K. Todorov, N. James and C. Hudelot, Multimedia Ontology Matching by Using Visual and Textual Modalities, Multimedia Tools and Applications, 2011, pp. 1-25
53. Y. Wang, W. Liu and D. Bell, Combining uncertain outputs from multiple ontology matchers, Scalable Uncertainty Management, 2007, pp. 201-214
54. B. Xu, D. Kang, J. Lu, Y. Li and J. Jiang, Mapping fuzzy concepts between fuzzy ontologies, in Knowledge-Based Intelligent Information and Engineering Systems, eds. R. Khosla, R. J. Howlett and L. C. Jain, Lecture Notes in Computer Science, Vol. 3683 (Springer, Berlin/Heidelberg, 2005), pp. 199-205
55. L. A. Zadeh, Fuzzy sets, Information and Control 8(3) (1965) 338-353
56. P. R. J. Östergard, A fast algorithm for the maximum clique problem, Discrete Appl. Math. 120 (2002) 197-207