Efficient Approximation for Counting of Formal Concepts Generated from FCA Context
The number of formal concepts generated from the input context is an important parameter in the cost functions of concept formation algorithms. The calculation of concept count for any arbitrary context is a hard, NP-complete problem and only rough approximation methods can be found in the literature to solve this problem. This paper introduces an efficient numerical approximation algorithm for contexts where attribute probabilities are independent from the objects instances. The preconditions required by the approximation method are usually met in the FCA applications, thus the proposed method provides an efficient tool for practical complexity analysis, too.
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Hivatkozás
MLA: Kovács, László. "Efficient Approximation for Counting of Formal Concepts Generated from FCA Context." Miskolc Mathematical Notes 19.2 (2018): 983-996.
APA: Kovács, L. (2018). Efficient Approximation for Counting of Formal Concepts Generated from FCA Context. Miskolc Mathematical Notes, 19(2), 983-996.
ISO690: KOVÁCS, László. Efficient Approximation for Counting of Formal Concepts Generated from FCA Context. Miskolc Mathematical Notes, 2018, 19.2: 983-996.
BibTeX:
@article{kovacs2018efficient,
title={Efficient Approximation for Counting of Formal Concepts Generated from FCA Context},
author={Kov{'a}cs, L{'a}szl{'o}},
journal={Miskolc Mathematical Notes},
volume={19},
number={2},
pages={983--996},
year={2018},
publisher={University of Miskolc, Hungary}
}