Abstract
In this paper, for the low similarity computation accuracy of concept in the field of agriculture ontology mapping, formal concept analysis theory and rough set theory are introduced to similarity computation. Jointly considering attribute hierarchies in concept lattice, the semantic hierarchy of the concepts are weighted differently, and the theory and methods of similarity calculation of rough formal concept in missing-value context is given. Finally, similarity computing model is prospected. Experimental results show the model has a high computational accuracy.
Fund projects: National High Technology Research and Development Program of China (No. 2006AA10Z249); National Natural Science Foundation of China (No. 30971091, 30800663).
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© 2011 IFIP International Federation for Information Processing
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Kai, W., Shao-Wen, L., You-Hua, Z., Chao, L. (2011). Research on the Theory and Methods for Similarity Calculation of Rough Formal Concept in Missing-Value Context. In: Li, D., Liu, Y., Chen, Y. (eds) Computer and Computing Technologies in Agriculture IV. CCTA 2010. IFIP Advances in Information and Communication Technology, vol 345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18336-2_52
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DOI: https://doi.org/10.1007/978-3-642-18336-2_52
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-18335-5
Online ISBN: 978-3-642-18336-2
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