Educing knowledge from text: semantic information extraction of spatial concepts and places

Abstract

Abstract. A growing body of geospatial research has shifted the focus from fully structured to semistructured and unstructured content written in natural language. Natural language texts provide a wealth of knowledge about geospatial concepts, places, events, and activities that needs to be extracted and formalized to support semantic annotation, knowledge-based exploration, and semantic search. The paper presents a web-based prototype for the extraction of geospatial entities and concepts, and the subsequent semantic visualization and interactive exploration of the extraction results. A lightweight ontology anchored in natural language guides the interpretation of natural language texts and the extraction of relevant domain knowledge. The approach is applied on three heterogeneous sources which provide a wealth of spatial concepts and place names.

Get Spatial from Non-Spatial Information: Inferring Spatial Information from Textual Descriptions by Conceptual Spaces

“…Although these descriptions rarely contain the spatial location of objects (e.g., in terms of postal addresses [13]), they may contain place names, spatial relations, and directions. Research on the extraction of spatial relations from textual content and natural languages has been growing rapidly in recent years [14][15][16]. Such studies aim at extracting spatial information in three forms that correspondingly answer three types of queries.…”