  In this chapter we discuss soft concept analysis, a study which identifies an
enriched notion of "conceptual scale" as developed in formal concept analysis
with an enriched notion of "linguistic variable" as discussed in fuzzy logic.
The identification "enriched conceptual scale" = "enriched linguistic variable"
was made in a previous paper (Enriched interpretation, Robert E. Kent). In this
chapter we offer further arguments for the importance of this identification by
discussing the philosophy, spirit, and practical application of conceptual
scaling to the discovery, conceptual analysis, interpretation, and
categorization of networked information resources. We argue that a linguistic
variable, which has been defined at just the right generalization of valuated
categories, provides a natural definition for the process of soft conceptual
scaling. This enrichment using valuated categories models the relation of
indiscernability, a notion of central importance in rough set theory. At a more
fundamental level for soft concept analysis, it also models the derivation of
formal concepts, a process of central importance in formal concept analysis.
Soft concept analysis is synonymous with enriched concept analysis. From one
viewpoint, the study of soft concept analysis that is initiated here extends
formal concept analysis to soft computational structures. From another
viewpoint, soft concept analysis provides a natural foundation for soft
computation by unifying and explaining notions from soft computation in terms
of suitably generalized notions from formal concept analysis, rough set theory
and fuzzy set theory.
