Abstract
Formal concept analysis (FCA) derives a hierarchy of concepts in a formal context that relates objects with attributes. This approach is very well aligned with the traditions of Frege, Saussure and Peirce, which relate a signifier (e.g. a word/an attribute) to a mental concept evoked by this word and meant to refer to a specific object in the real world. However, in the practice of natural languages as well as artificial languages (e.g. programming languages), the application context often constitutes a latent variable that influences the interpretation of a signifier. We present some of our current work that analyzes the usage of words in natural language in varying application contexts as well as the usage of variables in programming languages in varying application contexts in order to provide conceptual constraints on these signifiers.
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Notes
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NASA - NSSDC Photo Gallery Version: ftp://nssdcftp.gsfc.nasa.gov/photo_gallery/hi-res/planetary/venus/pvo_uv_790226.tiff, Public Domain, https://commons.wikimedia.org/w/index.php?curid=10914.
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Sketch of mace from https://commons.wikimedia.org/wiki/File:Boeheim_Morgenstern _01.jpg#/media/File:Boeheim_Morgenstern_01.jpg, Public domain.
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See [13] for a survey on the integration of description logics and formal concept analysis. It includes the representation of multiple formal contexts to represent concepts in non-hierarchical relationships.
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Staab, S. (2019). Concepts in Application Context. In: Cristea, D., Le Ber, F., Sertkaya, B. (eds) Formal Concept Analysis. ICFCA 2019. Lecture Notes in Computer Science(), vol 11511. Springer, Cham. https://doi.org/10.1007/978-3-030-21462-3_4
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