A Reuse-based Spatial Data Preparation Framework for Data Mining

نویسندگان

  • Vania Bogorny
  • Paulo Martins Engel
  • Luis Otávio Alvares
چکیده

The constant increase in use of geographic data in different application domains has resulted in large amounts of data stored in spatial databases and in the desire of data mining. Many solutions for spatial data mining have been proposed. Most create data mining languages or extend existing query languages to support data mining operations. This paper presents an interoperable framework for spatial data preparation for data mining. The approach is based on reuse of standard definitions such as Open GIS Consortium specifications, SQL query language, and well-established data mining toolkits. The proposed framework was implemented in the Java programming language and validated with real spatial databases and the Weka data mining toolkit.

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تاریخ انتشار 2005