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Ontology learning from text: a look back and into the future

journal contribution
posted on 2024-11-01, 10:42 authored by Wilson Wong, Wei Liu, Mohammed Bennamoun
Ontologies are often viewed as the answer to the need for inter-operable 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 fuelled 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.

History

Journal

ACM Computing Surveys

Volume

44

Number

20

Issue

4

Start page

1

End page

36

Total pages

36

Publisher

Association for Computing Machinery

Place published

United States

Language

English

Copyright

© 2012 ACM

Former Identifier

2006034546

Esploro creation date

2020-06-22

Fedora creation date

2012-12-10