We are interested in the intensive use of Factorial Correspondence Analysis (FCA) for large-scale content-based image retrieval. Factorial Correspondence Analysis, is a useful method for analyzing textual data, and we adapt it to images using the SIFT local descriptors. FCA is used to reduce dimensions and to limit the number of images to be considered during the search. Graphics Processing Uni...

Formal Concept Analysis (FCA) provides mathematical models, methods and algorithms for data analysis. However, by now there is no easily available program system, which would provide data analyst with unified, intelligible and transparent access to various external data sources with large amount of heterogeneous data for subsequent FCA-based knowledge discovery. The lack of such tools complicat...

Formal concept analysis (FCA) is built on a special type of Galois connections called polarities. We present new results in formal concept analysis and in Galois connections by presenting new Galois connection results and then applying these to formal concept analysis. We also approach FCA from the perspective of collections of formal contexts. Usually, when doing FCA, a formal context is fixed...

Formal concept analysis (FCA) is a solid mathematical framework to manage information based on logic and lattice theory. It defines two explicit representations of the knowledge present in dataset as concepts implications. This paper describes an R package called [fcaR](https://CRAN.R-project.org/package=fcaR) that implements FCA's core notions techniques. Additionally, it extension FCA fuzzy d...

One of the first models to be proposed as a document index for retrieval purposes was a lattice structure, decades before the introduction of Formal Concept Analysis. Nevertheless, the main notions that we consider so familiar within the community (“extension”, “intension”, “closure operators”, “order”) were already an important part of it. In the ’90s, as FCA was starting to settle as an epist...

The general topic of this thesis is the investigation of various notions of morphisms between logical deductive systems, motivated by the intuition that additional (categorical) structure is needed to model the interrelations of formal specifications. This general task necessarily involves considerations in various mathematical disciplines, some of which might be interesting in their own right ...

The autonomous pathway functions to promote flowering in Arabidopsis by limiting the accumulation of the floral repressor FLOWERING LOCUS C (FLC). Within this pathway FCA is a plant-specific, nuclear RNA-binding protein, which interacts with FY, a highly conserved eukaryotic polyadenylation factor. FCA and FY function to control polyadenylation site choice during processing of the FCA transcrip...

INTRODUCTION Development of an animal model of rheumatoid arthritis-interstitial lung disease (RA-ILD) and improved knowledge of the pathogenesis of RA-ILD may facilitate earlier diagnosis and the development of more effective targeted therapies. METHODS Adult male Wistar rats were studied in an adjuvant arthritis (AA) model induced by the injection of Freund's complete adjuvant (FCA). Rats w...

The application of Formal Concept Analysis (FCA) to Information Retrieval (IR) is twenty-five years old. Over this period, a number of papers have explored the potentials of FCA for various information finding tasks while several system prototypes have been made available for experimentation and testing. In this talk we survey what has been achieved so far, discussing lessons and implications f...

Flowering time control in plants involves integration of multiple signals. One of the signalling pathways in Arabidopsis involves a negative autoregulatory loop, in which the FCA protein together with FY promotes the choice of an alternative polyadenylation site within the FCA pre-mRNA to produce a transcript that does not encode a functional protein.