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[CL14] Ontology Learning from Databases: Some Efficient Methods to Discover Semantic Patterns in Data
Chapitres de Livre : Titre du livre: "Perspectives in Ontology Learning", October 2014, AKA / IOS Press. Serie , pp. 30, (isbn: 978-1-61499-379-7)Mots clés: Ontology Learning, Relational Databases, Natural Language Processing, Terminology Extraction
Résumé:
Databases are often considered as the most reliable sources for knowledge extraction. Methods and tools have been proposed to build ontologies from databases, mainly by exploiting relational schemas. However, the resulting ontologies are often far below expectations, especially in terms of expressivity. A significant part of the domain-specific semantics needed to build more expressive ontologies can only be recovered from the stored data. This chapter describes some semantic patterns that are frequently encountered in databases and provides a systematic description of data-driven methods to exploit these patterns for ontology learning.
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BibTeX
| @inbook { | |||
| CL14, | |||
| title | = | "{Perspectives in Ontology Learning}", | |
| chapter | = | "{Ontology Learning from Databases: Some Efficient Methods to Discover Semantic Patterns in Data}", | |
| author | = | "F. Cerbah and N. Lammari", | |
| year | = | 2014, | |
| publisher | = | "AKA / IOS Press. Serie ", | |
| pages | = | "30", | |
| isbn | = | "978-1-61499-379-7", | |
| } | |||
