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2015 | 25 | 2 | 377-387
Tytuł artykułu

Ant-based extraction of rules in simple decision systems over ontological graphs

Treść / Zawartość
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In the paper, the problem of extraction of complex decision rules in simple decision systems over ontological graphs is considered. The extracted rules are consistent with the dominance principle similar to that applied in the dominancebased rough set approach (DRSA). In our study, we propose to use a heuristic algorithm, utilizing the ant-based clustering approach, searching the semantic spaces of concepts presented by means of ontological graphs. Concepts included in the semantic spaces are values of attributes describing objects in simple decision systems.
Rocznik
Tom
25
Numer
2
Strony
377-387
Opis fizyczny
Daty
wydano
2015
otrzymano
2014-03-22
poprawiono
2014-08-08
poprawiono
2015-01-28
Twórcy
  • Department of Computer Science and Knowledge Engineering, University of Management and Administration, Akademicka 4, 22-400 Zamość, Poland
  • Department of Applied Informatics, University of Information Technology and Management, Sucharskiego 2, 35-225 Rzeszów, Poland
  • Department of Applied Informatics, University of Information Technology and Management, Sucharskiego 2, 35-225 Rzeszów, Poland
  • Department of Automatic Control and Biomedical Engineering, AGH University of Science and Technology, Mickiewicza 30, 30-059 Kraków, Poland
Bibliografia
  • Brachman, R. (1983). What IS-A is and isn't: An analysis of taxonomic links in semantic networks, Computer 16(10): 30-36.
  • Chaffin, R. and Herrmann, D.J. (1988). The nature of semantic relations: A comparison of two approaches, in M. Evens (Ed.), Relational Models of the Lexicon: Representing Knowledge in Semantic Networks, Cambridge University Press, New York, NY, pp. 289-334.
  • Deneubourg, J., Goss, S., Franks, N., Sendova-Franks, A., Detrain, C. and Chrétien, L. (1991). The dynamics of collective sorting: Robot-like ants and ant-like robots, Proceedings of the First International Conference on Simulation of Adaptive Behaviour: From Animals to Animats 1, MIT Press, Cambridge, MA, pp. 356-365.
  • Fernández, M.C., Menasalvas, E., Marban, O., Peña, J.M. and Millán, S. (2001). Minimal decision rules based on the Apriori algorithm, International Journal of Applied Mathematics and Computer Science 11(3): 691-704.
  • Greco, S., Matarazzo, B. and Słowiński, R. (2001). Rough sets theory for multicriteria decision analysis, European Journal of Operational Research 129(1): 1-47.
  • Handl, J., Knowles, J. and Dorigo, M. (2006). Ant-based clustering and topographic mapping, Artificial Life 12(1): 35-62.
  • Ishizu, S., Gehrmann, A., Nagai, Y. and Inukai, Y. (2007). Rough ontology: Extension of ontologies by rough sets, in M.J. Smith and G. Salvendy (Eds.), Human Interface and the Management of Information: Methods, Techniques and Tools in Information Design, Lecture Notes in Computer Science, Vol. 4557, Springer-Verlag, Berlin/Heidelberg, pp. 456-462.
  • Köhler, J., Philippi, S., Specht, M. and Rüegg, A. (2006). Ontology based text indexing and querying for the semantic web, Knowledge-Based Systems 19(8): 744-754.
  • Lumer, E. and Faieta, B. (1994). Diversity and adaptation in populations of clustering ants, Proceedings of the Third International Conference on Simulation of Adaptive Behaviour: From Animals to Animats 3, MIT Press, Cambridge, MA, pp. 501-508.
  • Midelfart, H. and Komorowski, J. (2002). A rough set framework for learning in a directed acyclic graph, in J.J. Alpigini, J.F. Peters, A. Skowron and N. Zhong (Eds.), Rough Sets and Current Trends in Computing, Lecture Notes in Computer Science, Vol. 2475, Springer-Verlag, Berlin/Heidelberg, pp. 144-155.
  • Milstead, J.L. (2001). Standards for relationships between subject indexing terms, in C.A. Bean and R. Green (Eds.), Relationships in the Organization of Knowledge, Kluwer Academic Publishers, Dordrecht, pp. 53-66.
  • Neches, R., Fikes, R., Finin, T., Gruber, T., Patil, R., Senator, T. and Swartout, W. (1991). Enabling technology for knowledge sharing, AI Magazine 12(3): 36-56.
  • Pancerz, K. (2012a). Dominance-based rough set approach for decision systems over ontological graphs, in M. Ganzha, L. Maciaszek and M. Paprzycki (Eds.), Proceedings of FedCSIS'2012, Wrocław, Poland, pp. 323-330.
  • Pancerz, K. (2012b). Toward information systems over ontological graphs, in J. Yao, Y. Yang, R. Słowiński, S. Greco, H. Li, S. Mitra and L. Polkowski (Eds.), Rough Sets and Current Trends in Computing, Lecture Notes in Artificial Intelligence, Vol. 7413, Springer-Verlag, Berlin/Heidelberg, pp. 243-248.
  • Pancerz, K. (2013a). Decision rules in simple decision systems over ontological graphs, in R. Burduk, K. Jackowski, M. Kurzyński, M. Woźniak and A. Zołnierek (Eds.), Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013, Advances in Intelligent Systems and Computing, Vol. 226, Springer International Publishing, Cham, pp. 111-120.
  • Pancerz, K. (2013b). Semantic relationships and approximations of sets: An ontological graph based approach, Proceedings of HSI'2013, Sopot, Poland, pp. 62-69.
  • Pancerz, K. (2014). Some remarks on complex information systems over ontological graphs, in A. Gruca, T. Czachórski and S. Kozielski (Eds.), Man-Machine Interactions 3, Advances in Intelligent Systems and Computing, Vol. 242, Springer International Publishing, Cham, pp. 55-62.
  • Pawlak, Z. (1991). Rough Sets: Theoretical Aspects of Reasoning about Data, Kluwer Academic Publishers, Dordrecht.
  • Roy, B. (1985). Méthodologie Multicritère d'Aide à la Décision, Economica, Paris.
  • Skowron, A. and Rauszer, C.M. (1992). The discernibility matrices and functions in information systems, in R.W. Slowinski (Ed.), Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory, Kluwer Academic Publishers, Dordrecht, pp. 331-362.
  • Slowinski, R. and Vanderpooten, D. (1996). A generalized definition of rough approximations, IEEE Transactions on Knowledge and Data Engineering 12(2): 331-336.
  • Storey, V.C. (1993). Understanding semantic relationships, The VLDB Journal 2(4): 455-488.
  • Tadeusiewicz, R. (2010). Place and role of intelligent systems in computer science, Computer Methods in Materials Science 10(4): 193-206.
  • Tadeusiewicz, R. (2011). Introduction to intelligent systems, in B. Wilamowski and J. Irvin (Eds.), The Industrial Electronics Handbook: Intelligent Systems, CRC Press, Boca Raton, FL, pp. 1-1-1-12.
  • Wikisaurus (2013). The homepage, http://en.wiktionary.org/wiki/ Wiktionary:Wikisaurus.
  • Winston, M. E., Chaffin, R. and Herrmann, D. (1987). A taxonomy of part-whole relations, Cognitive Science 11(4): 417-444.
  • Zadeh, L. (1996). Fuzzy logic = computing with words, IEEE Transactions on Fuzzy Systems 4(2): 103-111.
Typ dokumentu
Bibliografia
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Identyfikator YADDA
bwmeta1.element.bwnjournal-article-amcv25i2p377bwm
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