Domain specific ontologies from Linked Open Data (LOD)
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | |
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| _version_ | 1866912400162160640 |
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| author | Uceda-Sosa, Rosario Mihindukulasooriya, Nandana Kumar, Atul Bansal, Sahil Nagar, Seema |
| author_facet | Uceda-Sosa, Rosario Mihindukulasooriya, Nandana Kumar, Atul Bansal, Sahil Nagar, Seema |
| contents | Logical and probabilistic reasoning tasks that require a deeper knowledge of semantics are increasingly relying on general purpose ontologies such as Wikidata and DBpedia. However, tasks such as entity disambiguation and linking may benefit from domain specific knowledge graphs, which make it more efficient to consume the knowledge and easier to extend with proprietary content. We discuss our experience bootstrapping one such ontology for IT with a domain-agnostic pipeline, and extending it using domain-specific glossaries. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_22550 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Domain specific ontologies from Linked Open Data (LOD) Uceda-Sosa, Rosario Mihindukulasooriya, Nandana Kumar, Atul Bansal, Sahil Nagar, Seema Information Retrieval Logical and probabilistic reasoning tasks that require a deeper knowledge of semantics are increasingly relying on general purpose ontologies such as Wikidata and DBpedia. However, tasks such as entity disambiguation and linking may benefit from domain specific knowledge graphs, which make it more efficient to consume the knowledge and easier to extend with proprietary content. We discuss our experience bootstrapping one such ontology for IT with a domain-agnostic pipeline, and extending it using domain-specific glossaries. |
| title | Domain specific ontologies from Linked Open Data (LOD) |
| topic | Information Retrieval |
| url | https://arxiv.org/abs/2505.22550 |