Proceedings of the third annual conference on Autonomous Agents
Automatic object extraction from aerial imagery—a survey focusing on buildings
Computer Vision and Image Understanding
Efficient SVM Regression Training with SMO
Machine Learning
Retrieving and Semantically Integrating Heterogeneous Data from the Web
IEEE Intelligent Systems
Iterative record linkage for cleaning and integration
Proceedings of the 9th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Automatically and accurately conflating orthoimagery and street maps
Proceedings of the 12th annual ACM international workshop on Geographic information systems
Semantic integration in text: from ambiguous names to identifiable entities
AI Magazine - Special issue on semantic integration
Object fusion in geographic information systems
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Automated conflation of digital gazetteer data
International Journal of Geographical Information Science - Digital Gazetteer Research
Geo-ontology enrichment through reverse engineering
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
"Same, Same but Different" A Survey on Duplicate Detection Methods for Situation Awareness
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part II
Towards effective geographic ontology matching
GeoS'07 Proceedings of the 2nd international conference on GeoSpatial semantics
Geographic ontology matching with iG-match
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
A supervised machine learning approach for duplicate detection over gazetteer records
GeoS'11 Proceedings of the 4th international conference on GeoSpatial semantics
Geometrical DCC-Algorithm for merging polygonal geospatial data
ICCSA'10 Proceedings of the 2010 international conference on Computational Science and Its Applications - Volume Part I
Lo mejor de dos idiomas: cross-lingual linkage of geotagged wikipedia articles
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
A Comparison of String Similarity Measures for Toponym Matching
Proceedings of The First ACM SIGSPATIAL International Workshop on Computational Models of Place
Deduplicating a places database
Proceedings of the 23rd international conference on World wide web
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Due to the growing availability of geospatial data from a wide variety of sources, there is a pressing need for robust, accurate and automatic merging and matching techniques. Geospatial Entity Resolution is the process of determining, from a collection of database sources referring to geospatial locations, a single consolidated collection of 'true' locations. At the heart of this process is the problem of determining when two locations references match---i.e., when they refer to the same underlying location. In this paper, we introduce a novel method for resolving location entities in geospatial data. A typical geospatial database contains heterogeneous features such as location name, spatial coordinates, location type and demographic information. We investigate the use of all of these features in algorithms for geospatial entity resolution. Entity resolution is further complicated by the fact that the different sources may use different vocabularies for describing the location types and a semantic mapping is required. We propose a novel approach which learns how to combine the different features to perform accurate resolutions. We present experimental results showing that methods combining spatial and non-spatial features (e.g., location-name, location-type, etc.) together outperform methods based on spatial or name information alone.