A methodology for semi-automatic classification schema building

TL;DR

This paper presents a semi-automatic methodology for building classification schemas that combines typology creation from document clustering with schema refinement through logical operations.

Contribution

It introduces a novel combined approach using extensional clustering and intensional schema refinement for automatic document classification.

Findings

Effective typology generation from document clusters

Schema refinement through aggregation and generalization

Applicable to ontology and classification tasks

Abstract

This paper describe a methodology for semi-automatic classification schema definition (a classification schema is a taxonomy of categories useful for automatic document classification). The methodology is based on: (i) an extensional approach useful to create a typology starting from a document base, and (ii) an intensional approach to build the classification schema starting from the typology. The extensional approach uses clustering techniques to group together documents on the basis of a similarity measure, whereas the intensional approach uses different operations (aggregation, reduction, generalization specialization) to define classes. keywords: ontology, classification schema, fundamentum divisionis, cluster analysis classification task.