Ontology learning for the Semantic Web
Top Cited Papers
- 1 March 2001
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Intelligent Systems
- Vol. 16 (2), 72-79
- https://doi.org/10.1109/5254.920602
Abstract
The Semantic Web relies heavily on formal ontologies to structure data for comprehensive and transportable machine understanding. Thus, the proliferation of ontologies factors largely in the Semantic Web's success. The authors present an ontology learning framework that extends typical ontology engineering environments by using semiautomatic ontology construction tools. The framework encompasses ontology import, extraction, pruning, refinement and evaluation.Keywords
This publication has 15 references indexed in Scilit:
- Knowledge processes and ontologiesIEEE Intelligent Systems, 2001
- Learning from parsed sentences with INTHELEXPublished by Association for Computational Linguistics (ACL) ,2000
- Formal Concept AnalysisPublished by Springer Nature ,1999
- The Reengineering of Relational Databases based on Key and Data CorrelationsPublished by Springer Nature ,1998
- An information extraction core system for real world German text processingPublished by Association for Computational Linguistics (ACL) ,1997
- WordNetCommunications of the ACM, 1995
- Balanced cooperative modelingMachine Learning, 1993
- Acquisition of selectional patterns in sublanguagesMachine Translation, 1993
- Integrated knowledge acquisition architecturesJournal of Intelligent Information Systems, 1992
- Automatic acquisition of hyponyms from large text corporaPublished by Association for Computational Linguistics (ACL) ,1992