Ontology Learning System

AKA: Ontology Learning from Text System, Ontology Extraction System, Ontology Generation System, Ontology Acquisition System.
Context:
- It can extract textual data from a text document, corpus or website.
- It can range from being a Manual Ontology Learning System, to being a SemiautomaticOntology Learning System, to being an Automatic Ontology Learning System.
Example(s):
Counter-Example(s):
- an Ontology Editing System,
- an Ontology Management System,
- an Ontology Validation System,
- a Sentiment Analysis System,
- an Opinion Mining System.
See: Ontology Engineering, Ontology, Knowledge Base, Text Mining, Semantic Web, Machine Learning, CYC Project, Common Sense Knowledge, Text Corpus.

References

(Wikipedia, 2019) ⇒ https://en.wikipedia.org/wiki/Ontology_learning Retrieved:2019-6-30.
- Ontology learning (ontology extraction, ontology generation, or ontology acquisition) is the automatic or semi-automatic creation of ontologies, including extracting the corresponding domain's terms and the relationships between the concepts that these terms represent from a corpus of natural language text, and encoding them with an ontology language for easy retrieval. As building ontologies manually is extremely labor-intensive and time-consuming, there is great motivation to automate the process.
  Typically, the process starts by extracting terms and concepts or noun phrases from plain text using linguistic processors such as part-of-speech tagging and phrase chunking. Then statistical ^[1] ^[2] techniques are used to extract relation signatures, often based on pattern-based ^[3] or definition-based ^[4] hypernym extraction techniques.

↑ Navigli & Velardi (2004)
↑ Velardi et al., (2013)
↑ Marti A. Hearst. Automatic acquisition of hyponyms from large text corpora. In: Proceedings of the Fourteenth International Conference on Computational Linguistics, pages 539--545, Nantes, France, July 1992.
↑ R.Navigli, P. Velardi. Learning Word-Class Lattices for Definition and Hypernym Extraction.Proc.of the 48th Annual Meeting of the Association for Computational Linguistics (ACL 2010), Uppsala, Sweden, July11-16,2010, pp.1318-1327.

(Sammut & Webb, 2017) ⇒ (2017) "Ontology Learning". In: Sammut & Webb, (2017). DOI: 10.1007/978-1-4899-7687-1_959
- QUOTE: Different approaches have been used for building ontologies, most of them to date mainly using manual methods (Text Mining for the Semantic Web). An approach to building ontologies was set up in the CYC project, where the main step involved manual extraction of common sense knowledge from different sources. Ontology construction methodologies usually involve several phases including identifying the purpose of the ontology (why to build it, how will it be used, the range of the users), building the ontology, evaluation and documentation. Ontology learning relates to the phase of building the ontology using semiautomatic methods based on text mining or machine learning.