Context-Sensitive Qualitative Spatial Reasoning for Interpreting Vague Place Descriptions

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Volunteered Geographic Information (VGI) can be regarded to encompass a broad spectrum of sources for information, ranging from purposefully collected geo-referenced data to implicit geographical references, for example textual descriptions of geographic entities like "a park between the arms of the Regnitz river, near the village Bug". Enabling computer systems to benefit from the latter category of implicit information is particularly relevant since text-based communication is a very natural form of information exchange, in particular considering social media platforms, Tweets, or the Wikipedia encyclopedia. As a consequence, there exists manifoldly pieces of information that can serve several applications, and it may also serve as a tool to gain new insights into social aspects of utilization and conception of spatial environments. Before pieces of implicit geographic information contained in text can be exploited, geographic information content has first to be made explicit and interpreted with respect to existing geographical knowledge -- this puts a focus on spatial knowledge representation, reasoning, and querying techniques.This project will investigate qualitative spatial reasoning (QSR) techniques to capture context-sensitive vague spatial information in human-generated vague place descriptions and will develop algorithms that allow geographic databases to be queried using such descriptions.The aim of this project is to develop (1) a computational model to represent qualitative context-dependent vague spatial relations in symbolic statements that particularly considers mutually consistent interpretation of vague relation semantics, (2) reasoning algorithms capable of integrating several such statements, and (3) query algorithms that allow matching vaguely described places against a geographic database.