Generalizing and Processing Topological Data using Sentence Data Structure

San Kim, Eunjung Joo, Jusung Ha, Jaekwang Kim

Abstract: Data-processing methods have evolved because of the high demand due to the development of information technology. Specifically, data created by individuals are being generated very rapidly through social-media services, and thus, they assume importance in service personalization. Personal data involve very complex relations and various lists. It is difficult to develop a data system for complex relational lists, using the traditional relational-table model. There are several approaches to addressing this limitation in the relational-table model. The graph structure is one such emerging approach. In graph data, each object in the data constitutes a node, and relations between objects constitute links. The graph data structure has been used in commercial products, such as Google Cayley and Amazon Neptune. In this study, we generalize the graph data structure to a topological data structure and demonstrate a method to transform topological data into a sentence structure. We suggest the use of query functions and provide relevant examples.