Modern Information Retrieval
Geographical Information Retrieval with Ontologies of Place
COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
Core Elements of Digital Gazetteers: Placenames, Categories, and Footprints
ECDL '00 Proceedings of the 4th European Conference on Research and Advanced Technology for Digital Libraries
A Small Set of Formal Topological Relationships Suitable for End-User Interaction
SSD '93 Proceedings of the Third International Symposium on Advances in Spatial Databases
Towards topological consistency and similarity of multiresolution geographical maps
Proceedings of the 13th annual ACM international workshop on Geographic information systems
Hierarchy as a new data type for qualitative variables
Expert Systems with Applications: An International Journal
Geographic information retrieval by topological, geographical, and conceptual matching
GeoS'07 Proceedings of the 2nd international conference on GeoSpatial semantics
Spatio-textual indexing for geographical search on the web
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
Ontology-Based spatial query expansion in information retrieval
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, COA, and ODBASE - Volume Part II
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Geographic Information Ranking consists of measuring if a document (answer) is relevant to a spatial query. It is done by comparing characteristics in common between document and query. The most popular approaches compare just one aspect of geographical data (geographic properties, topology, among others). It limits the assessment of document relevance. Nevertheless, it can be improved when key characteristics of geographical objects are considered in the ranking (1) geographical attributes, (2) topological relations, and (3) geographical concepts. In this paper, we outline iRank a method that integrates these three aspects to rank a document. Ourapproach evaluates documents from three sources of information: GeoOntologies , dictionaries, and topology files. Relevance is measured according to three stages. In the first stage, the relevance is computed by processing concepts; in second stage relevance is calculated using geographic attributes. In the last stage, the relevance is measured by computing topologic relations. Thus, the main contribution of iRank is show that integration of three ranking criteria is better than when they are used in separate way.