An Application of Association Rules Discovery to Geographic Information Systems

No abstract is available for this paper.

• Publication year

  2000

• Venue

  European Conference on Principles of Data Mining and Knowledge Discovery

• Publication date

  2000-09-13

• Fields of study

  Geography, Computer Science, Geology

• Identifiers
  DOI 10.1007/3-540-45372-5_74
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• A progressive refinement approach to spatial data mining

  1999cited by this paper
• A bibliography of temporal, spatial and spatio-temporal data mining research

  1999cited by this paper
• Mining Association Rules in Multiple Relations

  1997cited by this paper
• Spatial Data Mining: A Database Approach

  1997cited by this paper
• Spatial Data Mining: Progress and Challenges

  1996cited by this paper
• Discovery of Spatial Association Rules in Geographic Information Databases

  1995cited by this paper
• Fast Algorithms for Mining Association Rules in Large Databases

  1994cited by this paper

• Comparison of Sentiment Analysis on Online Product Reviews Using Optimised RNN-LSTM with Support Vector Machine

  2022cites this paper
• Discovering of association rules without a minimum support threshold - coherent rules discovery

  2021cites this paper
• Proceso para el descubrimiento de asociaciones espaciales mediante subgrafos frecuentes

  2018cites this paper
• The SpatialARMED Framework: Handling Complex Spatial Components in Spatial Association Rule Mining

  2016cites this paper
• Rule Technologies: Foundations, Tools, and Applications

  2015cites this paper
• Learning Characteristic Rules in Geographic Information Systems

  2015cites this paper
• Behavior in Moodle System Using Datamining Technics

  2014cites this paper
• Mineral potential mapping for orogenic gold deposits in the Rio Maria granite greenstone terrane, southeastern Para State, Brazil

  2012cites this paper
• EXTRACTING SPATIAL ASSOCIATION RULES FROM THE MAXIMUM FREQUENT ITEMSETS BASED ON BOOLEAN MATRIX

  2012cites this paper
• Extracting spatial association rules from the maximum frequent itemsets based on Boolean matrix

  2011cites this paper
• Classification et évolution des tissus urbains à partir de données vectorielles

  2011cites this paper
• Classification des tissus urbains à partir de bases de données vectorielles - application à Strasbourg

  2010cites this paper
• Describing differences between overlapping databases

  2009cites this paper
• Describing Differences between Overlapping Databases

  2008cites this paper
• GOLD predictivity mapping in French Guiana using an expert‐guided data‐driven approach based on a regional‐scale GIS

  2008cites this paper
• Risk discovery of car-related crimes from urban spatial attributes using emerging patterns

  2007cites this paper
• Predictive mapping for copper-gold magmatic-hydrothermal systems in NW Argentina: Use of a regional-scale GIS, application of an expert-guided data-driven approach, and comparison with results from a continental-scale GIS

  2006cites this paper
• Utilisation des treillis de Galois pour l'extraction et la visualisation des règles d'association spatiales

  2006cites this paper
• The Use of the Galois lattice for the extraction and the visualization of the spatial association rules

  2006cites this paper
• Predicting gold-rich epithermal and porphyry systems in the central Andes with a continental-scale metallogenic GIS

  2004cites this paper
• Understanding and assessing European mineral resources - a new approach using GIS Central Europe

  2004cites this paper
• Knowledge Recovery for Continental-Scale Mineral Exploration by Neural Networks

  2003influential citation
• Mining maximal frequent itemsets by a boolean based approach

  2002cites this paper