From guod@sc.edu Fri Oct 3 16:30:54 2008 From: guod@sc.edu (Diansheng Guo) Date: Fri, 3 Oct 2008 08:30:54 -0700 (PDT) Subject: [SAM] AAG 2009 Session: Spatial Data Mining Message-ID: <342696.16564.qm@web65715.mail.ac4.yahoo.com> --0-324324393-1223047854=:16564 Content-Type: text/plain; charset=us-ascii ************************************************************************ AAG 2009 Session: Spatial Data Mining and Exploratory Data Analysis ************************************************************************ Organized by: Diansheng Guo (University of South Carolina) Jeremy Mennis (Temple University) Sponsored by: Geographic Information Science Specialty Group (pending) Spatial Analysis and Modeling Specialty Group (approved) Cartography Specialty Group (pending) The volume of available geographic data in various domains has increased dramatically due to the growing sophistication and ubiquity of geospatial technologies. Due to the size and complexity, effective analysis and use of these data demand innovative analytical approaches. Spatial data mining addresses this issue by focusing on the discovery, interpretation, and presentation of information embedded in very large and complex geographic data sets. This session invites research contributions in the theory, design, implementation, and application of data mining and exploratory data analysis techniques to spatial and spatio-temporal data. Potential topics include (but not limited to): * Computational algorithms for extracting patterns from spatial data sets * Geovisualization and exploratory analysis methods and applications * Approaches for analyzing high-dimensional and/or noisy spatial data sets * Approaches for analyzing spatio-temporal and path/network data types * Knowledge representation and semantics in spatial data mining and visualization * Applications of existing or new methods to social and/or physical science data * Applications of existing or new methods to support decision-making and planning * Collection and analysis of new types of geographic data (e.g. simulation data, activity data, sensor data, and mobile data) * Collection, fusion, and analysis of heterogeneous or multimedia geographic data (e.g. text, image, video, etc.) To present a paper in the session: * Register and submit your abstract online (http://www.aag.org/annualmeetings/). * Email your presenter identification number (PIN), paper title, and abstract to guod@sc.edu by October 14, 2008. ************************************************************************ --0-324324393-1223047854=:16564 Content-Type: text/html; charset=us-ascii
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AAG 2009 Session: Spatial Data Mining and Exploratory Data Analysis
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Organized by:
Diansheng Guo (University of South Carolina)
Jeremy Mennis (Temple University)
Sponsored by:
Geographic Information Science Specialty
Group (pending)
Spatial Analysis and Modeling Specialty
Group (approved)
Cartography Specialty Group (pending)
The volume of available geographic data in various domains has increased dramatically due to the growing sophistication and ubiquity of geospatial technologies. Due to the size and complexity, effective analysis and use of these data demand innovative analytical approaches. Spatial data mining addresses this issue by focusing on the discovery, interpretation, and presentation of information embedded in very large and complex geographic data sets. This session invites research contributions in the theory, design, implementation, and application of data mining and exploratory data analysis techniques to spatial and spatio-temporal data. Potential topics include (but not limited to):
To present a paper in the session:
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