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Building a Very Large Ontology from Medical Thesauri
- https://link.springer.com/chapter/10.1007/978-3-540-24750-0_7
- The emerging biomedical ontology currently comprises more than 240,000 conceptual entities and, hence, constitutes one of the largest formal knowledge bases ever built. …
Building a Very Large Ontology from Medical Thesauri
- https://link.springer.com/content/pdf/10.1007/978-3-540-24750-0_7.pdf?pdf=inline%20link
- which covers more than 60 medical thesauri and classifications (e.g., MESH, IeD, SNOMED, DIGITAL ANATOMIST). From a conceptual perspective, the UMLS can be divided into …
Building a Very Large Ontology from Medical Thesauri
- https://link.springer.com/chapter/10.1007/978-3-540-24750-0_7/cover/
- Medical knowledge from a comprehensive, though semantically shallow terminological repository, the UMLS, is transformed into a formally rigorous, expressive description …
Building a Very Large Ontology from Medical Thesauri
- https://www.semanticscholar.org/paper/Building-a-Very-Large-Ontology-from-Medical-Hahn-Schulz/bb8fc8f93d52270b8fba5246c8467bc6bf92f820
- This work reports on a large-scale knowledge conversion and curation case study, in which medical knowledge from a comprehensive, though semantically shallow terminological …
Building a Very Large Ontology from Medical Thesauri
- https://www.researchgate.net/publication/255665316_Building_a_Very_Large_Ontology_from_Medical_Thesauri
- The emerging biomedical ontology currently comprises more than 240,000 conceptual entities and, hence, constitutes one of the largest formal knowledge bases …
dblp: Building a Very Large Ontology from Medical …
- https://dblp.org/rec/books/sp/staabS2004/HahnS04
- Bibliographic details on Building a Very Large Ontology from Medical Thesauri. We are hiring! We are looking for additional members to join the dblp team. (more information) ...
Methodology to Build Medical Ontology from Textual …
- https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1839277/
- We also found limits in the comparison of the two methods: bringing together the hierarchies with automatic tools implies, on the one hand, more sophisticated pairing technics, and …
Building a Very Large Ontology from Medical Thesauri
- https://www.infona.pl/resource/bwmeta1.element.springer-e5884429-bd27-3e70-a54c-4ee51343b4ab
- This way, the broad coverage of the UMLS is combined with inference mechanisms for consistency and cycle checking. They are the key not only to proper cleansing of the …
Building a Very Large Ontology from Medical Thesauri
- https://researchr.org/publication/HahnS04
- Building a Very Large Ontology from Medical Thesauri. Udo Hahn, Stefan Schulz. Building a Very Large Ontology from Medical Thesauri. In Steffen Staab, Rudi Studer, …
Building a Very Large Ontology from Medical Thesauri.
- https://www.bibsonomy.org/bibtex/4b0caa910c738ce5a304b95a7a480cfc?lang=en
- This publication has not been reviewed yet. rating distribution. average user rating 0.0 out of 5.0 based on 0 reviews
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