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Izvorni znanstveni članak
https://doi.org/10.2498/cit.1002114

Exploring Attributes with Domain Knowledge in Formal Concept Analysis

Jonnalagadda Annapurna ; School of Computing Science and Engineering, VIT University, Vellore
Aswani Kumar Cherukuri ; School of Information Technology, VIT University, Vellore

Puni tekst: engleski, PDF (601 KB) str. 109-123 preuzimanja: 819* citiraj
APA 6th Edition
Annapurna, J. i Cherukuri, A.K. (2013). Exploring Attributes with Domain Knowledge in Formal Concept Analysis. Journal of computing and information technology, 21 (2), 109-123. https://doi.org/10.2498/cit.1002114
MLA 8th Edition
Annapurna, Jonnalagadda i Aswani Kumar Cherukuri. "Exploring Attributes with Domain Knowledge in Formal Concept Analysis." Journal of computing and information technology, vol. 21, br. 2, 2013, str. 109-123. https://doi.org/10.2498/cit.1002114. Citirano 07.03.2021.
Chicago 17th Edition
Annapurna, Jonnalagadda i Aswani Kumar Cherukuri. "Exploring Attributes with Domain Knowledge in Formal Concept Analysis." Journal of computing and information technology 21, br. 2 (2013): 109-123. https://doi.org/10.2498/cit.1002114
Harvard
Annapurna, J., i Cherukuri, A.K. (2013). 'Exploring Attributes with Domain Knowledge in Formal Concept Analysis', Journal of computing and information technology, 21(2), str. 109-123. https://doi.org/10.2498/cit.1002114
Vancouver
Annapurna J, Cherukuri AK. Exploring Attributes with Domain Knowledge in Formal Concept Analysis. Journal of computing and information technology [Internet]. 2013 [pristupljeno 07.03.2021.];21(2):109-123. https://doi.org/10.2498/cit.1002114
IEEE
J. Annapurna i A.K. Cherukuri, "Exploring Attributes with Domain Knowledge in Formal Concept Analysis", Journal of computing and information technology, vol.21, br. 2, str. 109-123, 2013. [Online]. https://doi.org/10.2498/cit.1002114

Sažetak
Recent literature reports the growing interests in data analysis using FormalConceptAnalysis (FCA), in which data is represented in the form of object and attribute relations. FCA analyzes and then subsequently visualizes the data based on duality called Galois connection. Attribute exploration is a knowledge acquisition process in FCA, which interactively determines the implications holding between the attributes. The objective of this paper is to demonstrate the attribute exploration to understand the dependencies among the attributes in the data. While performing this process, we add domain experts’ knowledge as background knowledge. We demonstrate the method through experiments on two real world healthcare datasets. The results show that the knowledge acquired through exploration process coupled with domain expert knowledge has better classification accuracy.

Ključne riječi
association rules; attribute exploration; background knowledge; concept lattice; formal concept analysis

Hrčak ID: 109447

URI
https://hrcak.srce.hr/109447

Posjeta: 1.064 *