Abstract
Global problems all occur at a particular location on or near the Earth’s surface. Sitting at the junction of artificial intelligence (AI) and big data, knowledge graphs (KGs) organize, interlink, and create semantic knowledge, thus attracting much attention worldwide. Although the existing KGs are constructed from internet encyclopedias and contain abundant knowledge, they lack exact coordinates and geographical relationships. In light of this, a geographical knowledge graph (GeoKG) construction method based on multisource data is proposed, consisting of a modeling schema layer and a filling data layer. This method has two advantages: (1) the knowledge can be extracted from geographic datasets; (2) the knowledge on multisource data can be represented and integrated. Firstly, the schema layer is designed to represent geographical knowledge. Then, the methods of extraction and integration from multisource data are designed to fill the data layer, and a storage method is developed to associate semantics with geospatial knowledge. Finally, the GeoKG is verified through linkage rate, semantic relationship rate, and application cases. The experiments indicate that the method could automatically extract and integrate knowledge from multisource data. Additionally, our GeoKG has a higher success rate of linking web pages with geographic datasets, and its exact coordinates have increased to 100%. This paper could bridge the distance between a Geographic Information System and a KG, thus facilitating more geospatial applications.
Highlights
knowledge graphs (KGs) have attracted a lot of attention worldwide, and play an essential role in artificial intelligence (AI)
General KGs lack geographical knowledge. Both geographic datasets and Baidu Baike are taken as data sources to extract geographical knowledge and semantics
The geographical knowledge graph (GeoKG) is verified through the linkage rate, coverage rate, and application cases
Summary
The KG was proposed by the Google Knowledge Graph project to devise a more intelligent search engine. It consists of concepts, entities, literature and relationships, and focuses on extracting and fusing knowledge from online encyclopedias. Taking the search sentence of “the length of the Yellow River” as an example, Google can return a knowledge card, and provide an accurate answer of 5464 km based on KG. When we search for “Yellow River” in the Google search engine, the related web pages will be presented on the left side, and the attributes (such as length, area, headstream, picture of the river, etc.) will be shown on the right side. In CNDBPedia [11], for example, three Chinese internet encyclopedias
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