The geoattributed entity extraction technology for visual representation of objects spatial relations based on automated schematic map generation

This paper considers the problem of extracting geoattributed entities from natural language texts to visualize the spatial relations of geographical objects. For visualization we use the technology of automated generation of schematic maps as subject-oriented components of geographic information systems. The paper describes the information technology that allows extracting geoattributed entities from natural language texts by combining several approaches. These are the neural network approach, the rule-based approach and the approach based on the use of lexico-syntactic patterns for the analysis of natural language texts. For data visualization we propose to use automated geocoding tools in conjunction with the capabilities of modern geographic information systems. The result of this technology is a cartogram that displays the spatial relations of the objects mentioned in the text.