Ontology Learning from Open Linked Data and Web Snippets
The Web of Open Linked Data (OLD) is a recommended best practice for exposing, sharing, and connecting pieces of data, information, and knowledge on the Semantic Web using URIs and RDF. Such data can be used as a training source for ontology learning from web textual contents in order to bridge the gap between structured data and the Web. In this paper, the authors propose a new method of ontology learning that consists in learning linguistic patterns related to OLD entities attributes from web snippets. Their insight is to use the Linked Data as a skeleton for ontology construction and for pattern learning from texts.