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Centralized models of these algorithms fail to process large-scale datasets due to the limitations of both software and hardware infrastructure. This limitation motivated us to develop the Distributed Terminological Decision Tree (DistTDT), a decentralized approach for inducing terminological decision trees that significantly improves the results of concept learning problems. We integrate a refinement operator into DistTDT to generate a set of subsumed concept candidates. Furthermore, we introduce a prototype for a distributed reasoner, which is necessary for class satisfiability checks, retrieving instances of a specified class, and performing entailment checks. Empirical evaluation demonstrates that the proposed model outperforms existing baselines by implementing enhancements to existing learning algorithms. DistTDT enables efficient processing of large-scale Web Ontology Language (OWL) datasets and scales horizontally. Finally, our approach outperforms a well-known centralized approach in terms of runtime performance and learning metrics, including matching rate, commission error rate, omission error rate, and induction rate. DistTDT is publicly available as an open-source extension integrated into the SANSA framework.<\/jats:p>","DOI":"10.1007\/s10115-026-02891-2","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T18:36:30Z","timestamp":1790188590000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["DistTDT: distributed terminological decision tree learning"],"prefix":"10.1007","volume":"68","author":[{"given":"Heba","family":"Mohamed","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"G\u00fcnter","family":"Kniesel-W\u00fcnsche","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jens","family":"Lehmann","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Said","family":"Fathalla","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,9,23]]},"reference":[{"key":"2891_CR1","doi-asserted-by":"publisher","unstructured":"Kulmanov M, Smaili FZ, Gao X, Hoehndorf R (2021) Semantic similarity and machine learning with ontologies. 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