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Detecting Important Patterns Using Conceptual Relevance Interestingness Measure
[article]
2021
arXiv
pre-print
Discovering meaningful conceptual structures is a substantial task in data mining and knowledge discovery applications. While off-the-shelf interestingness indices defined in Formal Concept Analysis may provide an effective relevance evaluation in several situations, they frequently give inadequate results when faced with massive formal contexts (and concept lattices), and in the presence of irrelevant concepts. In this paper, we introduce the Conceptual Relevance (CR) score, a new scalable
arXiv:2110.11262v1
fatcat:ep5v3xzgb5gevjn4rph2oblwta