The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Text mining and ontologies in biomedicine: Making sense of raw text
Abstract
The volume of biomedical literature is increasing at such a rate that it is becoming difficult to locate, retrieve and manage the reported information without text mining, which aims to automatically distill information, extract facts, discover implicit links and generate hypotheses relevant to user needs. Ontologies, as conceptual models, provide the necessary framework for semantic representation of textual information. The principal link between text and an ontology is terminology, which maps terms to domain-specific concepts. This paper summarises different approaches in which ontologies have been used for text-mining applications in biomedicine.
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Cites
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Relations in biomedical ontologies
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Cited by
Schmiedel, T., Müller, O., & vom Brocke, J. (2019) · Organizational Research Methods · doi:10.1177/1094428118773858 · Cited by 319
Information retrieval and text mining technologies for chemistry
Krallinger, M., Rabal, O., Lourenço, A., Oyarzabal, J., & Valencia, A. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00851 · Cited by 281
Semantic Web meets Integrative Biology: a survey
Chen, H., Yu, T., & Chen, J. Y. (2013) · Briefings in Bioinformatics · doi:10.1093/bib/bbs014 · Cited by 65
A novel somatic cancer gene-based biomedical document feature ranking and clustering model
Bikku, T., & Paturi, R. (2019) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2019.100188 · Cited by 15
Metadata
- Authors
- Spasic, I., Ananiadou, S., McNaught, J., & Kumar, A.
- Venue
- Briefings in Bioinformatics
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-01-01
- Volume
- 6
- Issue
- 3
- Pages
- 239-251
- ISSN
- 1467-5463 (ISSN-L)
- 1477-4054
- OpenAlex
- W2144949988
- Cited by
- 299
- References
- 40
- FWCI
- 4.26
- Type
- journal article
- Language
- en
- Open access
- closed
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- Spasic, I., Ananiadou, S., McNaught, J., & Kumar, A. (2005). Text mining and ontologies in biomedicine: Making sense of raw text. Briefings in Bioinformatics. https://doi.org/10.1093/bib/6.3.239
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
