On Relevance, Probabilistic Indexing and Information Retrieval
Journal of the ACM (JACM)
Document language models, query models, and risk minimization for information retrieval
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Relevance based language models
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
GeoVIBE: A Visual Interface for Geographic Digital Libraries
Visual Interfaces to Digital Libraries [JCDL 2002 Workshop]
GeoVSM: An Integrated Retrieval Model for Geographic Information
GIScience '02 Proceedings of the Second International Conference on Geographic Information Science
Indexing and ranking in Geo-IR systems
Proceedings of the 2005 workshop on Geographic information retrieval
A query-aware document ranking method for geographic information retrieval
Proceedings of the 4th ACM workshop on Geographical information retrieval
Spatial variation in search engine queries
Proceedings of the 17th international conference on World Wide Web
A comparison of geometric approaches to assessing spatial similarity for GIR
International Journal of Geographical Information Science
Retrieving address-based locations from the web
Proceedings of the 2nd international workshop on Geographic information retrieval
Estimating Risk of Picking a Sentence for Document Summarization
CICLing '09 Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing
Measuring Similarity of Geographic Regions for Geographic Information Retrieval
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Adaptive geospatially focused crawling
Proceedings of the 18th ACM conference on Information and knowledge management
Learning to rank for geographic information retrieval
Proceedings of the 6th Workshop on Geographic Information Retrieval
A probabilistic model of geographic relevance
Proceedings of the 6th Workshop on Geographic Information Retrieval
Concept based representations for ranking in geographic information retrieval
IceTAL'10 Proceedings of the 7th international conference on Advances in natural language processing
The University of Lisbon at GeoCLEF 2006
CLEF'06 Proceedings of the 7th international conference on Cross-Language Evaluation Forum: evaluation of multilingual and multi-modal information retrieval
A Visual Interactive System for Spatial Querying and Ranking of Geographic Regions
Proceedings of the 13th International Conference on Knowledge Management and Knowledge Technologies
Criteria of query-independent page significance in geospatial web search
Proceedings of the 7th Workshop on Geographic Information Retrieval
Geographical queries beyond conventional boundaries: regional search and exploration
Proceedings of the 7th Workshop on Geographic Information Retrieval
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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.