Spatially-Aware Information Retrieval with Graph-Based Qualitative Reference Models

May 2003

Proceedings of the Sixteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2003)

Volume

Proceedings of the Sixteenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2003)

All Papers

Geo-referenced information is used by a growing number of "spatially-aware" tools in different application areas, including tourism, marketing, environmental management, and mobile location based services. To support such applications, methods for "spatially-aware" information retrieval that do not only consider the thematic, but also the spatial relevance of information items are needed. In addition to information "directly" geo-referenced with the help of coordinates, there exist large amounts of information that is geo-referenced "indirectly" through place names. Place name lists, or gazetteers, link place names to coordinate space, but do offer only limited options for the spatial representation of place names and reasoning about spatial relevance. In this paper, we outline the concept of qualitative spatial reference models that use regional approximations of place names in support of reasoning about spatial relevance. The core components of such reference models are graph-based abstractions of polygonal standard reference tessellations, together with their intrinsic decomposition hierarchies. Reasoning about spatial relevance is based on a metric that evaluates the vertical and horizontal proximity of spatial entities.