The aim of the GeoRich workshop is to provide a unique forum for discussing in depth the challenges, opportunities, novel techniques and applications on modeling, managing, searching and mining rich geo-spatial data, in order to fuel scientific research on big spatial data applications.
Proceeding Downloads
Similarity search over enriched geospatial data
Enriched geospatial data refers to geospatial entities associated with additional information from various sources, such as textual, numerical or temporal. Exploring such data involves multi-criteria search and ranking across several heterogeneous ...
Geopriv4j: an open source repository for practical location privacy
The breach of users' location privacy can be catastrophic. To prevent privacy breaches, numerous location privacy methods have been developed in the last two decades. However, they have not been widely adopted in location-based applications. As a result,...
Evaluating computational geometry libraries for big spatial data exploration
With the rise of big spatial data, many systems were developed on Hadoop, Spark, Storm, Flink, and similar big data systems to handle big spatial data. At the core of all these systems, they use a computational geometry library to represent points, ...
Boosting toponym interlinking by paying attention to both machine and deep learning
Toponym interlinking is the problem of identifying same spatio-textual entities within two or more different data sources, based exclusively on their names. It comprises a significant task in geospatial data management and integration with application ...
Index Terms
- Proceedings of the Sixth International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data
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Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
GeoRich '20 | 9 | 4 | 44% |
GeoRich '17 | 10 | 8 | 80% |
GeoRich '16 | 18 | 8 | 44% |
GeoRich'15 | 13 | 5 | 38% |
Overall | 50 | 25 | 50% |