  Formal Concept Analysis and its associated conceptual structures have been
used to support exploratory search through conceptual navigation. Relational
Concept Analysis (RCA) is an extension of Formal Concept Analysis to process
relational datasets. RCA and its multiple interconnected structures represent
good candidates to support exploratory search in relational datasets, as they
are enabling navigation within a structure as well as between the connected
structures. However, building the entire structures does not present an
efficient solution to explore a small localised area of the dataset, for
instance to retrieve the closest alternatives to a given query. In these cases,
generating only a concept and its neighbour concepts at each navigation step
appears as a less costly alternative. In this paper, we propose an algorithm to
compute a concept and its neighbourhood in extended concept lattices. The
concepts are generated directly from the relational context family, and possess
both formal and relational attributes. The algorithm takes into account two RCA
scaling operators. We illustrate it on an example.
