Organizing the Unorganized: A Novel Approach for Transferring a Taxonomy of Labels into Flat-Labeled Document Collections

This paper presents a novel pipeline for transforming flat-labeled text collections into a hierarchical structure, which involves leveraging simple yet effective similarity methods that account for both lexical and semantic criteria to associate labels from disparate sources. Our approach employs a custom similarity measure, the Reinforced Edit Similarity, to identify probable correspondences based on lexical similarities. A subsequent semantic alignment and validation phase is then performed using an automatic classification mechanism. Preliminary results attest to the effectiveness of our proposal. These results are obtained from the research group of the University of Torino in the NGUPP project