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Ontology is one of the oldest terminologies in physics and is used to describe the origin and most essential attributes of all things in the world. With the development of contemporary science, ontology was given a specific definition and then introduced into the computer science as a conceptual model to describe the relationship between objects. In the past decade, the algorithms and applications in the ontology-related field have attracted the attention of many scholars. In this work, a support vector machines based multi-dividing ontology learning algorithm is proposed. We pay attention to the similarity of topological indices in chemical graph theory, and apply SVM-based multi-dividing ontology learning algorithms to give some calculation results of similarity between topological indices.