The paper represents a first attempt to formalize the get-specific document classification algorithm and to fully automate it through reasoning in a propositional concept language without requiring user involvement or a training dataset. We follow a knowledge-centric approach and convert a natural language hierarchical classification into a formal classification, where the labels are defined in the concept language. This allows us to encode the get-specific algorithm as a problem in the concept language. The reported experimental results provide evidence of practical applicability of the proposed approach.
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