The survey of co-occurrence analysis method in the structural depiction of scientific domain of ontology
Appearance of semantic web and consequently, ontologies have led to a novel revolution in information retrieval field regarding their semantic structure. Web creation and emergence, on one side, has caused a faster information growth and data bank development, on the other side, in a way that the traditional methods of information retrieval and text processing are no longer adequate to meet the individual needs for necessary information. The present authors, due to the significance of ontology visualizations, analyzed the thematic content of this field in the Web of Science database by the words co-occurrence analysis. According to this method, the subjects of ontology visualization were extracted and their interrelationships were directly obtained from thematic content. Thus, the current study is to survey the thematic content of fields and subfields of ontology and the intra-relationships of these subfields. Then, the usage and applicability of this method is analyzed in depicting this scientific field structure. This study is practical in its type and various methods of taxonomy, co-words analysis and network analysis are used. So, some series of published essays on ontology in WOS database from 2000 to 2016 including 17,015 records were extracted. After probing the key terms of these essays, the terms of ontology and its subfields were identified; after acquiring the thematic pattern of this field by VOS viewer software, the tasks of analyzing the data collected from maps, formed clustering and classification and their interrelationships were done.