Abstract
The purpose of this article is to analyze semantic relations based on graph-independent structural analysis in VocBench. The mix-method of deductive and inductive approach is adapted in operating the research methodology, especially for data collection. The research data are structural domains of semantic relations in ontologies. The data resource is the authoritative agricultural ontology, VocBench, that has been originated by Food and Agricultural organization (FAO), United Nation. VocBench includes around 40000 concepts. The sample size is around 1500 concepts. Sampling technique used is the stratified random sampling. The data analysis results are employed in the SPSS and Excel software using descriptive and proportional analysis. The research results reveal that the taxonomic relations cover a wide area in VocBench. Moreover, the overloading was not seen in the usage of non-taxonomic relations. The high frequency in the usage of the semantic relations’ output might be implied the possibility of the width (i.e., exhaustivity) in semantic network in VocBench.
Highlights
The structural dimensions are represented as a graph in ontology evaluation [1] based on Conceptual Graph (CG) [2] or Conceptual Graph Theory [3]
The results clearly showed that the amount of taxonomic relations covered three-quarter of the total semantic relations in VocBench and this finding confirmed the results of the first research question
The core or subject field which can be clarified by taxonomic relations covers a wide area in VocBench
Summary
The structural dimensions are represented as a graph in ontology evaluation [1] based on Conceptual Graph (CG) [2] or Conceptual Graph Theory [3]. Graphs are labeled with two types of nodes, subject and object nodes [4], that are concepts and conceptual relations [3] underlying graph structure [5, 6] or ontology-graph structure [7, 8] or graph-based ontology representation [9]. In this case, structural analyses are limited to the analysis of ontology structure with respect to the graph-dependent approach.
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