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Evidence Sources, Methods and Use Cases for Learning Lightweight Domain Ontologies

Evidence Sources, Methods and Use Cases for Learning Lightweight Domain Ontologies

Albert Weichselbraun, Gerhard Wohlgenannt, Arno Scharl
Copyright: © 2011 |Pages: 15
ISBN13: 9781609606251|ISBN10: 1609606256|EISBN13: 9781609606268
DOI: 10.4018/978-1-60960-625-1.ch001
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MLA

Weichselbraun, Albert, et al. "Evidence Sources, Methods and Use Cases for Learning Lightweight Domain Ontologies." Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances, edited by Wilson Wong, et al., IGI Global, 2011, pp. 1-15. https://doi.org/10.4018/978-1-60960-625-1.ch001

APA

Weichselbraun, A., Wohlgenannt, G., & Scharl, A. (2011). Evidence Sources, Methods and Use Cases for Learning Lightweight Domain Ontologies. In W. Wong, W. Liu, & M. Bennamoun (Eds.), Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances (pp. 1-15). IGI Global. https://doi.org/10.4018/978-1-60960-625-1.ch001

Chicago

Weichselbraun, Albert, Gerhard Wohlgenannt, and Arno Scharl. "Evidence Sources, Methods and Use Cases for Learning Lightweight Domain Ontologies." In Ontology Learning and Knowledge Discovery Using the Web: Challenges and Recent Advances, edited by Wilson Wong, Wei Liu, and Mohammed Bennamoun, 1-15. Hershey, PA: IGI Global, 2011. https://doi.org/10.4018/978-1-60960-625-1.ch001

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Abstract

By providing interoperability and shared meaning across actors and domains, lightweight domain ontologies are a cornerstone technology of the Semantic Web. This chapter investigates evidence sources for ontology learning and describes a generic and extensible approach to ontology learning that combines such evidence sources to extract domain concepts, identify relations between the ontology’s concepts, and detect relation labels automatically. An implementation illustrates the presented ontology learning and relation labeling framework and serves as the basis for discussing possible pitfalls in ontology learning. Afterwards, three use cases demonstrate the usefulness of the presented framework and its application to real-world problems.

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