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The paper introduces a novel conceptualization algorithm optimized for a distributed, Big Data environment. The proposed method uses a concept generation module based on clique detection in the context graph. The presented work proposes a novel incremental version of the Bron-Kerbosch maximal clique detection method. The efficiency of the method is evaluated with random context tests. The presented incremental model is even comparable with the usual batch methods. The analysis of the cliquedoi:10.12700/aph.13.2.2016.2.8 fatcat:op44d4t6rvaj7o3isf7tb7waiu