Abstract
Fuzzy set theory has proved to be a successful paradigm to extend the database relational model, augmenting its skill to capture uncertaintly. This capability may be consider in two levels: the data itself and the constraints defined to adjust the database schema to the real system. When constraints are considered, it is necessary to design methods to reason about it and not only a way to express them. This situation leads to a ambitious goal: the design of automated reasoning methods. Highly-expressive data models are not useful without an automated reasoning method. In this work we introduce an automated method to infer with fuzzy functional dependencies over a high level generalization of the relational model and provide its completeness result.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Codd, E.F.: The relational model for database management: version 2. Addison-Wesley Longman Publishing Co., Inc., Boston (1990)
Cordero, P., Enciso, M., Mora, A., de Guzmán, I.P., Rodríguez-Jiménez, J.M.: Specification and inference of fuzzy attributes. In: FOCI, pp. 107–114 (2011)
Abiteboul, S., et al.: The lowell database research self-assessment. Communications of the ACM 48, 111–118 (2005); ACM ID: 1060718
Giardina, C., Sack, I., Sinha, D.: Fuzzy field relational database. Report 8332, Elect. Engng. and Computer Science Dept., Stevens Institute of Technology, Hoboken, NJ (1983)
Baldwin, J.: Knowledge engineering using a fuzzy relational inference language. In: Proc. IFAC Conf. on Fuzzy Information, Knowledge Representation, and Decision Processes, Marseille, France, pp. 15–23 (1983)
Prade, H., Testemale, C.: The connection between lipskios approach to incomplete information data bases and zadeh’s possibility theory. In: Proc. Int. Conf. Systems Meth., pp. 402–408 (1982)
Prade, H., Testemale, C.: Generalizing database realtional algebra for the treatment of incomplete or uncertain information and vague queries. Information Sciences 34, 115–143 (1984)
Buckles, B.P., Perty, F.: A fuzzy representation of data for relational databases. Fuzzy Sets and Systems 7, 213–216 (1982)
Buckles, B.P., Perty, F.: Fuzzy databases and their applications. In: Fuzzy Inform. Decision Process, pp. 361–371 (1982)
Buckles, B.P., Perty, F.: Uncertainty models in information and database systems. J. Inform. Sci. 11, 77–87 (1985)
Yahia, S.B., Ounalli, H., Jaoua, A.: An extension of classical functional dependency: dynamic fuzzy functional dependency. Information Sciences 119, 219–234 (1999)
Tyagi, B., Sharfuddin, A., Dutta, R., Tayal, D.K.: A complete axiomatization of fuzzy functional dependencies using fuzzy function. Fuzzy Sets and Systems 151, 363–379 (2005)
Bělohlávek, R., Vychodil, V.: Data tables with similarity relations: Functional dependencies, complete rules and non-redundant bases. In: Li Lee, M., Tan, K.-L., Wuwongse, V. (eds.) DASFAA 2006. LNCS, vol. 3882, pp. 644–658. Springer, Heidelberg (2006)
Sözat, M.I., Yazici, A.: A complete axiomatization for fuzzy functional and multivalued dependencies in fuzzy database relations. Fuzzy Sets and Systems 117, 161–181 (2001)
Cordero, P., Enciso, M., Mora, A., de Guzmán, I.P.: A complete logic for fuzzy functional dependencies over domains with similarity relations. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M. (eds.) IWANN 2009, Part I. LNCS, vol. 5517, pp. 261–269. Springer, Heidelberg (2009)
Cordero, P., Enciso, M., Mora, A., de Guzmán, I.P., Rodríguez-Jiménez, J.M.: An efficient algorithm for reasoning about fuzzy functional dependencies. In: Cabestany, J., Rojas, I., Joya, G. (eds.) IWANN 2011, Part II. LNCS, vol. 6692, pp. 412–420. Springer, Heidelberg (2011)
Medina, J., Ojeda-Aciego, M.: Dual multi-adjoint concept lattices. Information Sciences 225, 47–54 (2013)
Medina, J., Ojeda-Aciego, M., Ruiz-Calviño, J.: Fuzzy logic programming via multilattices. Fuzzy Sets and Systems 158, 674–688 (2007)
Raju, K.V.S.V.N., Majumdar, A.K.: Fuzzy functional dependencies and lossless join decomposition of fuzzy relational database systems. ACM Trans. Database Syst. 13, 129–166 (1988)
Belohlavek, R., Vychodil, V.: Relational model of data over domains with similarities: An extension for similarity queries and knowledge extraction. In: IEEE International Conference on Information Reuse and Integration, pp. 207–213 (2006)
Cordero, P., Enciso, M., Mora, A., de Guzmán, I.P.: A complete logic for fuzzy functional dependencies over t-norms. In: XV Spanish Conference on Fuzzy Logic and Technology, pp. 205–210 (2010)
Cordero, P., Enciso, M., Mora, A., de Guzmán, I.P.: Reasoning about fuzzy functional dependencies. In: XIV Spanish Conference on Fuzzy Logic and Technology, pp. 121–126 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Rodríguez-Jiménez, J.M., Cordero, P., Enciso, M., Mora, A. (2013). Automated Inference with Fuzzy Functional Dependencies over Graded Data. In: Rojas, I., Joya, G., Cabestany, J. (eds) Advances in Computational Intelligence. IWANN 2013. Lecture Notes in Computer Science, vol 7903. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38682-4_29
Download citation
DOI: https://doi.org/10.1007/978-3-642-38682-4_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38681-7
Online ISBN: 978-3-642-38682-4
eBook Packages: Computer ScienceComputer Science (R0)