The paper represents a first attempt to formalize the getspecific 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. © Springer-Verlag Berlin Heidelberg 2007.
Formalizing the Get-Specific Document Classification Algorithm
Giunchiglia, Fausto;Zaihrayeu, Ilya;Kharkevich, Uladzimir
2007-01-01
Abstract
The paper represents a first attempt to formalize the getspecific 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. © Springer-Verlag Berlin Heidelberg 2007.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione



