Relevance and Ranking in Geographic Information Retrieval

Geographic Information Retrieval (GIR) is a specialized branch of traditional Information Retrieval (IR), which deals with the information related to geographic locations. One of the main challenges of GIR is to quantify the spatial relevance of documents and generate a pertinent ranking of the results according to the spatial information needs of user. Most of the current methods judge the relevance of documents just based on textual and spatial similarity with the query, and ranked the results with a linear combination of these similarity measures. We consider relevance ranking as a much more dynamic problem stemming from real world application such as location based mobile services, where user not only seek information but there is a decision making involved with the search i.e. to visit the location. In this paper we discuss current ranking phenomenon in geographic information retrieval, present different relevant parameters based on our initial study, and argue for the need of a formal relevance framework and ranking mechanism for geographical information retrieval. We approach GIR ranking as a spatial decision problem to support user’s activity, and propose the idea to explore decision-theoretic framework and probabilistic representation for geo relevance formalization.