Concept lattices built on noisy data tend to be large and hence hard to interpret. We introduce several measures that can be used in selecting relevant concepts and discuss how the...
Mikhail Klimushkin, Sergei A. Obiedkov, Camille Ro...
Given Boolean data sets which record properties of objects, Formal Concept Analysis is a well-known approach for knowledge discovery. Recent application domains, e.g., for very lar...
Abstract. We address the problem of selecting a subset of the most relevant features from a set of sample data in cases where there are multiple (equally reasonable) solutions. In ...
The paper addresses the problem of concept location in source code by presenting an approach which combines Formal Concept Analysis (FCA) and Latent Semantic Indexing (LSI). In th...
We are designing new data mining techniques on boolean contexts to identify a priori interesting bi-sets (i.e., sets of objects or transactions associated to sets of attributes or ...