TaBIIC2: Interactive Building of Ontological Taxonomies using Weighted Self-Organizing Maps
The paper presents TaBIIC2, a tool designed for the interactive construction of ontological taxonomies using weighted self-organizing maps. This approach aims to bridge the gap between manual and automatic methods for building taxonomies from tabular data. By identifying clusters and their definitions, the tool offers users more control over the taxonomy-building process.
- ▪TaBIIC2 enables the progressive and interactive construction of taxonomies.
- ▪The tool uses weighted self-organizing maps for clustering.
- ▪It aims to provide a balance between manual analysis and automatic methods.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.24899 |
| Publication time | Tue, 26 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-26T04:07:43.013Z |
| Last seen | 2026-05-26T04:07:43.013Z |
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Computer Science > Artificial Intelligence arXiv:2605.24899 (cs) [Submitted on 24 May 2026] Title:TaBIIC2: Interactive Building of Ontological Taxonomies using Weighted Self-Organizing Maps Authors:Mathieu d'Aquin View a PDF of the paper titled TaBIIC2: Interactive Building of Ontological Taxonomies using Weighted Self-Organizing Maps, by Mathieu d'Aquin View PDF HTML (experimental) Abstract:Ontologies represent the conceptual knowledge of a domain. At the core of an ontology is the taxonomy of concepts and subconcepts that represent specific entities, which can be complex to build. In many cases, information is available in the form of records describing the characteristics of relevant entities, i.e., tabular data.
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