Departing the ontology layer cake

Abel Browarnik*, Oded Maimon

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

5 Scopus citations


In this chapter we analyze Ontology Learning and its goals, as well as the input expected when learning ontologies - peer-reviewed scientific papers in English. After reviewing the Ontology Learning Layer Cake model's shortcomings we suggest an alternative model based on linguistic knowledge. The suggested model would find the meaning of simple components of text - statements. From them it is easy to derive cases and roles that map the reality as a set of entities and relationships or RDF triples, somehow equivalent to Entity-relationship diagrams. Time complexity for the suggested ontology learning framework is constant (O(1)) for a sentence, and O(n) for an ontology with n sentences. We conclude that the Ontology Learning Layer Cake is not adequate for Ontology Learning from text.

Original languageEnglish
Title of host publicationModern Computational Models of Semantic Discovery in Natural Language
PublisherIGI Global
Number of pages37
ISBN (Electronic)9781466686915
ISBN (Print)1466686901, 9781466686908
StatePublished - 17 Jul 2015


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