A Systematic Study for Organizing Research Topics in Ontology Data Mining Domain

Ontology has played a significant role in various domains for the organization of computer-managed knowledge in recent years. Ontology is used to organize and classify objects in certain domains so that ontology can maximize new knowledge at a more detailed level. One of the domains that apply ontology is the data mining domain. Combining these two knowledge fields is targeted to represent the formal knowledge generated in the data mining process. One of them is that the ontology can help choose the right algorithm or technology so that the ontology can improve the data mining process results. To research in this field, it is necessary to compile, map and analyze the literature on the current state of the data mining ontology by looking at the contributions made from research journals and conferences originating from several relevant electronic databases. Systematic mapping study is a method to achieve this goal by integrating automatic and manual searches from various sources by developing a classification scheme. In this article, the Systematic mapping study starts with 12,819 articles from 1998 to 2019, and then the inclusion and exclusion criteria are carried out into 74 articles selected for review. The review has examined how papers are distributed annually. The material has been generated with the greatest contribution, an overview of the present state of the research, and the identification of gaps and prospective future avenues. The review provides an integrated and consolidated body of knowledge in the data mining ontology domain that can be used as a starting point for research to explore possible ideas from the topic of data mining ontology research.