Representing uncertain concepts in rough description logics via contextual indiscernibility relations

CEUR Workshop Proceedings

Volumn 423, Issue , 2008, Pages

  Fanizzi, Nicola ^a   D'Amato, Claudia ^a   Esposito, Floriana ^a   Lukasiewicz, Thomas ^b  

^a UNIVERSITY OF BARI   (Italy)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CONCEPT DEFINITIONS; DESCRIPTION LOGIC; EQUIVALENCE RELATIONSHIP; INDISCERNIBILITY; INDISCERNIBILITY RELATION; LOWER AND UPPER APPROXIMATIONS; SIMILARITY MEASURE; UNCERTAIN KNOWLEDGE;

FORMAL LANGUAGES;

DATA DESCRIPTION;

EID: 84885795412     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (16)

1. Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P., eds.: The Description Logic Handbook. Cambridge University Press (2003)
2. Lukasiewicz, T., Straccia, U.: Managing uncertainty and vagueness in description logics for the Semantic Web. Journal of Web Semantics (2008) in press.
3. Pawlak, Z.: Rough Sets: Theoretical Aspects of Reasoning About Data. Kluwer Academic Publishers (1991)
4. Doherty, P., Grabowski, M., Lukaszewicz, W., Szalas, A.: Towards a framework for approximate ontologies. Fundamenta Informaticae 57 (2003) 147-165
5. Schlobach, S., Klein, M.C.A., Peelen, L.: Description logics with approximate definitions - precise modeling of vague concepts. In: Proceedings of the 20th International Joint Conference on Artificial Intelligence (IJCAI 2007). (2007) 557-562
6. d'Amato, C., Fanizzi, N., Esposito, F.: Query answering and ontology population: An inductive approach. In: Proceedings of the 5th European Semantic Web Conference (ESWC 2008). Volume 5021 of LNCS, Springer (2008) 288-302
7. Mitchell, T.: Machine Learning. McGraw-Hill (1997)
8. Fanizzi, N., d'Amato, C., Esposito, F.: Randomized metric induction and evolutionary conceptual clustering for semantic knowledge bases. In: Proceedings of the 16th International Conference on Knowledge Management (CIKM 2007), ACM Press (2007) 51-60
9. Goldstone, R., Medin, D., Halberstadt, J.: Similarity in context. Memory and Cognition 25 (1997) 237-255
10. Donini, F., Lenzerini, M., Nardi, D., Nutt, W.: An epistemic operator for description logics. Artificial Intelligence 100 (1998) 225-274
11. Zezula, P., Amato, G., Dohnal, V., Batko, M.: Similarity Search - The Metric Space Approach. Advances in Database Systems. Springer (2007)
12. Hirano, S., Tsumoto, S.: An indiscernibility-based clustering method. In: 2005 IEEE International Conference on Granular Computing, IEEE Computer Society (2005) 468- 473
13. Fanizzi, N., d'Amato, C., Esposito, F.: Conceptual clustering for concept drift and novelty detection. In: Proceedings of the 5th European Semantic Web Conference (ESWC 2008). Volume 5021 of LNCS, Springer (2008) 318-332
14. Iannone, L., Palmisano, I., Fanizzi, N.: An algorithm based on counterfactuals for concept learning in the Semantic Web. Applied Intelligence 26 (2007) 139-159
15. Lehmann, J., Hitzler, P.: A refinement operator based learning algorithm for the ALC description logic. In: Proceedings of the 17th International Conference on Inductive Logic Programming (ILP 2007). Volume 4894 of LNCS, Springer (2008) 147-160
16. Fanizzi, N., d'Amato, C., Esposito, F.: DL-FOIL: Concept learning in description logics. In: Proceedings of the 18th International Conference on Inductive Logic Programming (ILP 2008). Volume 5194 of LNCS, Springer (2008) 107-121