Modern Information Retrieval
Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
Intelligent Systems and Soft Computing: Prospects, Tools and Applications
Geographical Information Retrieval with Ontologies of Place
COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
Georeferencing: The Geographic Associations of Information (Digital Libraries and Electronic Publishing)
Entity resolution in geospatial data integration
GIS '06 Proceedings of the 14th annual ACM international symposium on Advances in geographic information systems
The role of ontology in improving gazetteer interaction
International Journal of Geographical Information Science - Digital Gazetteer Research
An agenda for the next generation gazetteer: geographic information contribution and retrieval
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Bottom-Up Gazetteers: Learning from the Implicit Semantics of Geotags
GeoS '09 Proceedings of the 3rd International Conference on GeoSpatial Semantics
The quality of geospatial context
QuaCon'09 Proceedings of the 1st international conference on Quality of context
Multi-source toponym data integration and mediation for a meta-gazetteer service
GIScience'10 Proceedings of the 6th international conference on Geographic information science
A supervised machine learning approach for duplicate detection over gazetteer records
GeoS'11 Proceedings of the 4th international conference on GeoSpatial semantics
Weighted multi-attribute matching of user-generated points of interest
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
A Comparison of String Similarity Measures for Toponym Matching
Proceedings of The First ACM SIGSPATIAL International Workshop on Computational Models of Place
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A digital gazetteer (DG) is a spatial dictionary of named and typed places in some environment, typically the near-surface of the Earth. DGs are proliferating in number and sophistication with the popularity of location-based services such as GoogleEarth, MapQuest, and OnStar. The essential utility of a DG is to translate between formal and informal systems of place referencing, i.e. between the ad hoc names and qualitative type classifications assigned to places, on the one hand, and quantitative locations for them, on the other. Frequently, it is necessary to consult and combine results from multiple sources of gazetteer data, which is tedious for humans and currently not done by machines. Thus, a fundamental challenge with DGs is conflation: merging gazetteer data so that place identity is preserved. The challenge can be met using a computational approach modelled on human behaviour, focusing first on places' geometries (since disjoint places cannot be the same), second on their type categories, and finally on their names. This article details a troika of metrics that mimic the human cognitive process, together with operational procedures for automated conflation of DG data using them. By way of demonstration, both abstract and practical results of conflation for the Lake Tahoe Basin of California and Nevada are presented.