Database Primitives for Spatial Data Mining

Abstract: Spatial data mining algorithms heavily depend on the efficient processing of neighborhood relations since the neighbors of many objects have to be investigated in a single run of a typical algorithm. Therefore, providing general concepts for neighborhood relations as well as an efficient implementation of these concepts will allow a tight integration of spatial data mining algorithms with a spatial database management system. This will speed up both, the development and the execution of spatial data mining algorithms. In this paper, we define neighborhood graphs and paths and a small set of database primitives for their manipulation. Furthermore, we introduce neighborhood indices to speed up the processing of our database primitives. We implemented the database primitives on top of a commercial spatial database management system. The effectiveness and efficiency of the proposed approach was evaluated by using an analytical cost model and an extensive experimental study on a g...

• Type: Conference
• Year: 1999
• Where: BTW
• Authors: Martin Ester, Stefan Grundlach, Hans-Peter Kriegel, Jörg Sander
• Keywords: BTW 1999, Data Mining Algorithms, Database, Spatial Data Mining, Spatial Database Management