Abstract
In this paper we illustrate application of many valued context for extracting dependences from complex data sets. While the classical binary approach clearly indicates relationships among objects and attributes it still does not provide any information on the degrees to which an object possesses an attribute. Many valued contexts allow inclusion of more detailed description on such dependences. A specific data set is considered by working with both binary and many-valued contents. The latter one definitely provides a better overview of the dependences among objects and attributes.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Belohlavek, R.: Lattices generated by fuzzy relations. Tatra Mountains Mathematical Publ., Publications 16, 11–19 (1999)
Bruno, J.E.: Assessing the knowledge base of students: An information theoretic approach to testing. Journal of Measurement and Evaluation in Counseling and Development 19(3), 116–130 (1986)
Davey, B.A., Priestley, H.A.: Introduction to lattices and order. Cambridge University Press, Cambridge (2005)
Fum, D., Stocco, A.: Outcome Evaluation and Procedural Knowledge in Implicit Learning. In: Proceedings of the 25th Annual Meeting of the Cognitive Science Society, pp. 456–431 (2003)
Ganter, B., Wille, R.: Formal Concept Analysis - Mathematical Foundations. Springer (1999)
Guan, J., Wang, J.: Evaluation and interpretation of knowledge production efficiency. Evaluation 59(1), 131–155 (2004)
Klosgen, W., Zytkow, J.: Handbook of data mining and knowledge discovery. Oxford University Press, Inc., New York (2002)
Liu, S., Lin, Y.: Introduction to Grey Systems Theory. Understanding Complex Syst. 68, 1–18 (2011)
Messai, N., Devignes, M., Napoli, A., Sme-Tabbone, M.: Many-Valued Concept Lattices for Conceptual Clustering and Information Retrieval. In: ECAI, pp. 127–131 (2008)
Wille, R.: Concept lattices and conceptual knowledge systems. Computers Mathem. Applic. 23(6-9), 493–515 (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Encheva, S. (2012). Approximation of Specific Properties of Complex Objects. In: Lee, G., Howard, D., Kang, J.J., Ślęzak, D. (eds) Convergence and Hybrid Information Technology. ICHIT 2012. Lecture Notes in Computer Science, vol 7425. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32645-5_63
Download citation
DOI: https://doi.org/10.1007/978-3-642-32645-5_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32644-8
Online ISBN: 978-3-642-32645-5
eBook Packages: Computer ScienceComputer Science (R0)