Abstract

In this paper, we propose an approach for an FCA-based knowledge extraction process relying on the collaboration between humans and machines. Evaluation of the results is performed on the lattice by experts through an interactive process where they may specify their wishes for changes using a set of predefined operations. Thus, the system then may suggest several strategies to reach their goal. In such an interactive and iterative process, the system converges towards a knowledge model close to the experts’ needs. We illustrate the process on a small preliminary experiment.