The Knowledge Graph is a successful application of knowledge engineering, an important branch of artificial intelligence, in the context of big data. Together with big data and deep learning, knowledge graphs have become one of the core driving forces behind the development of the internet and artificial intelligence. Based on this background, the Research Report of Knowledge Graph provides a brief overview of this topic, including the following contents:
The concept and research overview of knowledge graphs. It elaborates on the concept and classification of knowledge graphs and introduces the development process of knowledge engineering in four stages.
Knowledge graph technology. It divides into five subfields: knowledge representation and modeling, knowledge acquisition, knowledge fusion, knowledge graph query reasoning, and knowledge graph applications, and introduces the technologies applied in each field.
Introduction of experts in the field of knowledge graphs. Based on information from the AMiner data platform, it organizes five subfields of knowledge graphs, focusing on the research directions and representative articles of scholars in each subfield, aiming to provide an analytical basis for academia and industry regarding knowledge graph technologies and scholars, while introducing the basic concepts, research, and application directions of knowledge graph technology to institutions interested in this field, such as government agencies, universities, and enterprises. This includes the global distribution of top scholars, migration patterns, distribution of scholar institutions, h-index analysis, and detailed introductions of highly cited scholars in the past decade based on the AMiner evaluation system during the development of knowledge graphs.
Applications of knowledge graphs. It introduces the applications of general knowledge graphs and domain-specific knowledge graphs. It discusses the technical construction and research status of domain knowledge graphs in five areas: e-commerce, library information, corporate business, shipping investment, and biomedicine, from the perspectives of graph construction and knowledge application.
Trends in knowledge graph research. It analyzes the trends and characteristics of knowledge graph development. Based on the AMiner data platform, it conducts a visual analysis of recent research hotspots in the field of knowledge graphs and predicts future research directions in this area.
Source: Internet
Reprinted from Teacher Training Alliance
