Proceedings of the 1 st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics ( DMG ) 2010 offered under the auspices of the 18 th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

Foreword for the special issue of selected papers from the 1st ACM SIGSPATIAL Workshop on Security and Privacy in GIS and LBS

The first Workshop on Security and Privacy in GIS and LBS (SPRINGL 2008) was organized on November 4, 2008 at Irvine (CA) in conjunction with the SIGSPATIAL International Conference on Advances in Geographic Information Systems (ACM GIS 2008). The goal of the SPRINGL workshop series is to provide a forum for researchers working in the area of geospatial data security and privacy. Both security ...

Proceedings of the 1 st ACM SIGSPATIAL International Workshop on Data Mining for Geoinformatics

Polygons can serve an important role in the analysis of georeferenced data as they provide a natural representation for particular types of spatial objects and in that they can be used as models for spatial clusters. This paper claims that polygon analysis is particularly useful for mining related, spatial datasets. A novel methodology for clustering polygons that have been extracted from diffe...

ACM SIGSPATIAL International Workshop on Computational Models of Place, COMP 2013, November 5, 2013, Orlando, Florida, USA

Editorial Letters on Similarity Search in Metric Spaces Fundamentals of the Problem

ACM SIGSPATIAL addresses issues related to the acquisition, management, and processing of spatially-related information with a focus on algorithmic, geometric, and visual considerations. The scope includes, but is not limited to, geographic information systems. For more details and membership information for ACM SIGSPATIAL as well as for accessing the newsletters please visit The SIGSPATIAL Spe...

Subset Scanning for Event and Pattern Detection

group on knowledge discovery and data mining, Boston, pp 71–80 Hand DJ, Mannila H, Smyth P (2001) Principles of data mining. MIT, Cambridge Hershberger J, Shrivastava N, Suri S (2006) Cluster hulls: a technique for summarizing spatial data streams. In: Proceedings of IEEE international conference on data engineering, Atlanta, p 138 Hulten G, Spencer L, Domingos P (2001) Mining timechanging data...