Hashing by Proximity to Process Duplicates in Spatial Databases

In a spatial database, an object may extend arbitrarily in space. As a result, many spatial data structures e.g., the quadtree, the cell tree, the R+-tree represent an object by partitioning it into multiple, yetsimple, pieces, each of which is stored separately inside the data structure. Many operations on these data structures are likely to produce duplicate results because of the multiplicity of object pieces. A novel approach for duplicate processing based on proximity of spatial objects is presented. This is di erent from conventional duplicate elimination in database systems because, with spatial databases, di erent pieces of the same object can span multiple buckets of the underlying data structure. Example algorithms are presented to perform duplicate processing using proximity for a quadtree representation of line segments and arbitrary rectangles. The complexity of the algorithms is seen to depend on a geometric classi cation of di erent instances of the spatial objects. By ...

• Type: Conference
• Year: 1994
• Where: CIKM
• Authors: Walid G. Aref, Hanan Samet
• Keywords: CIKM 1994, Data Structure, Duplicate Processing, Information Management, Spatial