Geographic Knowledge Graph Summarization

Geographic knowledge graphs can have an important role in delivering interoperability, accessibility and the demands of conceptualization in geographic information science (GIS). However, the massive amount of accompanying information and the enormous diversity of geographic knowledge graphs limits their applicability and hinders the widespread adoption of this useful structured knowledge. This book, Geographic Knowledge Graph Summarization, focuses on the ways in which geographic knowledge graphs can be digested and summarized. Such a summarization would relieve the burden of information overload for end users and reduce data storage, as well as speeding up queries and eliminating ‘noise’. The book introduces the general concept of geospatial inductive bias and explains the different ways in which this idea can be used in the summarization of geographic knowledge graphs.The book breaks up the task of summarization into separate but related components, and after an introduction and a brief overview of concepts and theories, Chapters 3, 4 and 5 explore hierarchical place type structure, multimedia leaf nodes, and general relation and entity components respectively. Chapter 6 presents a spatial knowledge map interface which illustrates the effectiveness of summarization.The book integrates top-down knowledge engineering and bottom-up knowledge learning methods, and will do much to promote awareness of this fascinating area and related issues.

Geographic knowledge graphs can have an important role in delivering interoperability, accessibility and the demands of conceptualization in geographic information science (GIS). However, the massive amount of accompanying information and the enormous diversity of geographic knowledge graphs limits their applicability and hinders the widespread adoption of this useful structured knowledge. This book, Geographic Knowledge Graph Summarization, focuses on the ways in which geographic knowledge graphs can be digested and summarized. Such a summarization would relieve the burden of information overload for end users and reduce data storage, as well as speeding up queries and eliminating ‘noise’. The book introduces the general concept of geospatial inductive bias and explains the different ways in which this idea can be used in the summarization of geographic knowledge graphs. The book breaks up the task of summarization into separate but related components, and after an introduction and a brief overview of concepts and theories, Chapters 3, 4 and 5 explore hierarchical place type structure, multimedia leaf nodes, and general relation and entity components respectively. Chapter 6 presents a spatial knowledge map interface which illustrates the effectiveness of summarization. The book integrates top-down knowledge engineering and bottom-up knowledge learning methods, and will do much to promote awareness of this fascinating area and related issues.