초록

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Abstract ▼ AI-Helper

There have been many works for developing spatial indexing and clustering methods for efficiently accessing a large volume of GIS data. To reduce I/O access time, It is necessary to support a clustering of logically related 2-dimensional data on the 1-dimensional disk. This paper presents a new clu...

There have been many works for developing spatial indexing and clustering methods for efficiently accessing a large volume of GIS data. To reduce I/O access time, It is necessary to support a clustering of logically related 2-dimensional data on the 1-dimensional disk. This paper presents a new clustering method on the extended Quad-tree which does not fragment any spatial object A number of clustering algorithms based on the gravity of geometry, the reference point of geometry, the overlap area are devised and evaluated. The result of performance evaluation of this methods is shown.