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Machine Learning for Map Interpretation: An Intelligent Tool for Environmental Planning.

, , , and . Applied Artificial Intelligence, 11 (7-8): 673-696 (1997)

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Discovery of spatial association rules in geo-referenced census data: A relational mining approach., , , , and . Intell. Data Anal., 7 (6): 541-566 (2003)Mining Cluster-Based Models of Time Series for Wind Power Prediction., , , and . SEBD, page 9-20. (2014)Discovering Geographic Knowledge: The INGENS System., , , and . ISMIS, volume 1932 of Lecture Notes in Computer Science, page 40-48. Springer, (2000)Generating Logic Descriptions for the Automated Interpretation of Topographic Maps., , , , and . GREC, volume 2390 of Lecture Notes in Computer Science, page 200-210. Springer, (2001)Relational Clustering with Discrete Spatial Structure., , , , and . SEBD, page 149-160. (2005)Empowering a GIS with inductive learning capabilities: the case of INGENS., , , , and . Computers, Environment and Urban Systems, 27 (3): 265-281 (2003)Wind Power Forecasting Using Time Series Cluster Analysis., , , and . Discovery Science, volume 8777 of Lecture Notes in Computer Science, page 276-287. Springer, (2014)On Homogeneity Evaluation and Seed Selection in Clustering Relational Data., , , and . SEBD, page 471-478. (2007)Geographic Knowledge Discovery in INGENS: An Inductive Database Perspective., , , , , and . ICDM Workshops, page 326-331. IEEE Computer Society, (2008)First-Order Rule Induction for the Recognition of Morphological Patterns in Topographic Maps., , , and . MLDM, volume 2123 of Lecture Notes in Computer Science, page 88-101. Springer, (2001)