Abstract
Semantic Web-based technologies have become extremely popular and its a success that has spread across many domains, additional to the computer science domain. Nevertheless, the reusability aspects associated with the created and available semantic knowledge models are very low. The main bottleneck associated with this issue is, the difficulty associated in understanding the complex schema of a knowledge model created and barriers associated with querying the knowledge models using SPARQL or SQWRL query formulations. This research emphasizes on proposing a verbalizer which can go beyond existing Controlled Natural Language (CNL) type verbalizers and to verbalizer knowledge stored in a knowledge model file written in either RDF or OWL format, despite its domain and schematics.
Highlights
Ontologies are domain rich conceptualizations [1]
The initial idea of ontologies was elicited from the concept of Semantic Web by Tim BernersLee for the first time [3]
The main emphasis of this research is to come up with a generalized verbalizer, which can extract knowledge from ontologies despite their domain and schema as well as regardless of whether they are written in Resource Description Framework (RDF) or Ontology Web Language (OWL) formats
Summary
Ontologies are domain rich conceptualizations [1]. That is the definition given for ontologies by Spasic et al in [1]. The initial idea of ontologies was elicited from the concept of Semantic Web by Tim BernersLee for the first time [3]. Though the idea initially emerged in 2001, by 2013, almost more than 4 million web domains have incorporated semantic web technologies to their web sites [4]. This clearly depicts the massive growth of semantic web across the entire globe proving its remarkable success. As claimed by Feigenbaum in [5] and Kashyap in [12] the noteworthy feature related to semantic webs utmost success is the potential of both human and machine readability of semantic webs knowledge representations
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