The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Ontology learning from text: A look back and into the future
Abstract
Ontologies are often viewed as the answer to the need for interoperable semantics in modern information systems. The explosion of textual information on the Read/Write Web coupled with the increasing demand for ontologies to power the Semantic Web have made (semi-)automatic ontology learning from text a very promising research area. This together with the advanced state in related areas, such as natural language processing, have fueled research into ontology learning over the past decade. This survey looks at how far we have come since the turn of the millennium and discusses the remaining challenges that will define the research directions in this area in the near future.
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Cites
An introduction to latent semantic analysis
Landauer, T. K., Foltz, P. W., & Laham, D. (1998) · Discourse Processes · doi:10.1080/01638539809545028 · Cited by 4,880
Cited by
A Survey on the Explainability of Supervised Machine Learning
Burkart, N., & Huber, M. F. (2021) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.12228 · Cited by 1,008
Ambert, K. H., Cohen, A. M., Burns, G. A. P. C., Boudreau, E., & Sonmez, K. (2013) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2013.00038 · Cited by 6
Metadata
- Authors
- Wong, W., Liu, W., & Bennamoun, M.
- Venue
- ACM Computing Surveys
- Published
- 2012-08
- Volume
- 44
- Issue
- 4
- Pages
- 1-36
- ISSN
- 0360-0300 (ISSN-L)
- 1557-7341
- OpenAlex
- W2124436241
- Cited by
- 397
- References
- 1
- FWCI
- 38.00
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wong, W., Liu, W., & Bennamoun, M. (2012). Ontology learning from text: A look back and into the future. ACM Computing Surveys. https://doi.org/10.1145/2333112.2333115
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