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Characteristic Summarization of Concept Lattices

Formal Concept Analysis is a mathematically well-founded theory used for (among others) computing concept lattices from data. However, concept lattices induced via FCA tend to be overwhelming in size and complexity, potentially leading to unwarranted overhead in subsequent informational tasks.
This talk discusses a probabilistic approach to deriving concept lattice summarizations that are concise, yet still structurally sound and characteristic of the underlying dataset. The talk concludes in an outlook into future research directions.

03.05.2018 - 10:15
B 016