Journal Publication

  • Guo, D. (2009). "Flow Mapping and Multivariate Visualization of Large Spatial Interaction Data", IEEE Transactions on Visualization and Computer Graphics, 15(6), pp. 1041-1048.
  • Guo, D. & J. Mennis (2009). "Spatial data mining and geographic knowledge discovery-An introduction", Computers, Environment and Urban Systems, 33(6) pp. 403-408.
  • Liao, K., D. Guo (2008). "A Clustering-Based Approach to a Capacitated Facility Location Problem", Transactions in GIS.12(3), pp. 323–339.
  • Guo, D. (2008). "Regionalization with Dynamically Constrained Agglomerative Clustering and Partitioning (REDCAP)", International Journal of Geographical Information Science. 22(7), pp. 801-823.
  • Chen, J., A.M. MacEachren, and D. Guo (2008). "Supporting the Process of Exploring and Interpreting Space-Time, Multivariate Patterns: The Visual Inquiry Toolkit", Cartography and Geographic Information Science. 35(1), pp. 33-50.
  • Guo, D. (2007). "Visual Analytics of Spatial Interaction Patterns for Pandemic Decision Support", International Journal of Geographical Information Science, 21(8), pp. 859-877.
  • Guo, D., K. Liao, M. Morgan (2007). "Visualizing Patterns in a Global Terrorism Incident Database", Environment and Planning B: Planning and Design. 34, pp. 767-784.
  • Guo, D. and M. Gahegan (2006). "Spatial Ordering and Encoding for Geographic Data Mining and Visualization", Journal of Intelligent Information Systems, 27(3), pp.243-266.
  • Guo, D., J. Chen, A. M. MacEachren, and K. Liao (2006). "A Visualization System for Spatio-Temporal and Multivariate Patterns (VIS-STAMP)", IEEE Transactions on Visualization and Computer Graphics, 12(6), pp. 1461-1474.
  • Guo, D., M. Gahegan, A.M. MacEachren, and B. Zhou (2005). "Multivariate Analysis and Geovisualization with an Integrated Geographic Knowledge Discovery Approach", Cartography and Geographic Information Science. 32(2), pp. 113-132.

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The materials distributed on this website since 2008 are based upon work partially supported by the National Science Foundation under Grant No. 0748813. Any opinions, findings and conclusions or recomendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation (NSF).