Fuzzy and rough formal concept analysis: A survey

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Abstract

Formal Concept Analysis (FCA) is a mathematical technique that has been extensively applied to Boolean data in knowledge discovery, information retrieval, web mining, etc. applications. During the past years, the research on extending FCA theory to cope with imprecise and incomplete information made significant progress. In this paper, we give a systematic overview of the more than 120 papers published between 2003 and 2011 on FCA with fuzzy attributes and rough FCA. We applied traditional FCA as a text-mining instrument to 1072 papers mentioning FCA in the abstract. These papers were formatted in pdf files and using a thesaurus with terms referring to research topics, we transformed them into concept lattices. These lattices were used to analyze and explore the most prominent research topics within the FCA with fuzzy attributes and rough FCA research communities. FCA turned out to be an ideal metatechnique for representing large volumes of unstructured texts. © 2013 Taylor & Francis.

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Poelmans, J., Ignatov, D. I., Kuznetsov, S. O., & Dedene, G. (2014). Fuzzy and rough formal concept analysis: A survey. International Journal of General Systems, 43(2), 105–134. https://doi.org/10.1080/03081079.2013.862377

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