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A new FCA algorithm enabling analyzing of complex and dynamic data sets

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Abstract

Analyzing data with the use of Formal Concept Analysis (FCA) enables complex insights into hidden relationships between objects and features in a studied system. Several improvements in this research area, such as Fuzzy FCA or L-Fuzzy Concepts, bring the possibility to analyze data with a certain rate of indeterminacy. However, the usage of FCA on larger complex data brings several problems relating to the time-complexities of FCA algorithms and the size of generated concept lattices. The fuzzyfication of FCA emphasizes the mentioned problems. This article describes significant improvements of a selected FCA algorithm. The primary focus was given on the system of an effective data storage. The binary data was stored with the use of finite automata that leads to the lower memory consumption. Moreover, the better querying performance was achieved. Next, we focused on the inner process of the computation of all formal concepts. All improvements were integrated into a new FCA algorithm that can be used to analyze more complex data sets.

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Notes

  1. More precisely, formal objects a formal attributes of the context.

  2. Note that not all of the algorithms are indicated in the table.

  3. An element that has only one direct upper neighbour is called join-irreducible and an element that has only one direct lower neighbour is called meet-irreducible.

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Authors and Affiliations

  1. Department of Computer Science, VŠB-Technical University of Ostrava, 17. listopadu 15, Ostrava, The Czech Republic

    Petr Gajdoš & Václav Snášel

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  1. Petr Gajdoš
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  2. Václav Snášel
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Correspondence to Petr Gajdoš.

Additional information

Communicated by I. Zelinka.

This article has been elaborated in the framework of the IT4Innovations Centre of Excellence project, reg. no. CZ.1.05/1.1.00/02.0070 funded by Structural Funds of the European Union and the state budget of the Czech Republic. The work is partially supported by Grant of SGS No. SP2013/70, VŠB - Technical University of Ostrava, The Czech Republic. This work was also supported by the Bio-Inspired Methods: research, development and knowledge transfer project, reg. no. CZ.1.07/2.3.00/20.0073 funded by the Operational Programme Education for Competitiveness, co-financed by ESF and the state budget of the Czech Republic.

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Gajdoš, P., Snášel, V. A new FCA algorithm enabling analyzing of complex and dynamic data sets. Soft Comput 18, 683–694 (2014). https://doi.org/10.1007/s00500-013-1176-6

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