Knowledge Graph Essentials and Key Technologies

Abstract

In recent decades, the amount of information that humankind has accumulated has increased tremendously. People cannot analyze it effectively using simple algorithms, and data structures due to these approaches do not understand the se¬mantics of the data. Thus, there is a need for such a data structure that would store a massive number of entities that would be accessible and easy to understand for machines, and moreover, saves the semantics. One efficient kind of structure is a knowledge graph, which quite recently ap¬peared and became the subject of research for the last few years due to its interesting and sophisticated architecture. The peak of knowledge graph interest came at the time when Google introduced their Knowledge Graph technology in 2012, and since then, it has become apparent what this concept of a knowledge graph is. However, it is still unclear how to use this technology in practice due to the small number of existing infor¬mation on this theme. In this paper, we introduce and review all steps of knowledge graph implementation. In addition to that, this article in¬cludes information about problems that need to be solved for having its instance of the knowledge graph; also, we consider machine learning em¬bedding methods to analyze knowledge graph structure, practical steps for KG usage, and so on.

Keywords

• knowledge graph
• embedding
• semantic knowledge graph
• anthology