Mining for Unknown Unknowns
This addresses a conceptual and practical challenge in data mining and decision-making, offering a novel approach to uncover hidden risks or opportunities.
The paper tackles the problem of identifying unknown unknowns, which are unforeseen relevant contingencies, by introducing a framework based on Formal Concept Analysis to systematically search for them.
Unknown unknowns are future relevant contingencies that lack an ex ante description. While there are numerous retrospective accounts showing that significant gains or losses might have been achieved or avoided had such contingencies been previously uncovered, getting hold of unknown unknowns still remains elusive, both in practice and conceptually. Using Formal Concept Analysis (FCA) - a subfield of lattice theory which is increasingly applied for mining and organizing data - this paper introduces a simple framework to systematically think out of the box and direct the search for unknown unknowns.