Reverse Approximate Queries in Spatial Databases

Reverse approximate queries in spatial databases relax the rigid requirement of k value in spatial reverse queries, increasing the influential accuracy for the query point. Reverse approximate queries consist of reverse approximate nearest neighbour (RANN) query and spatial reverse approximate top (SRAT) query. RANN was studied in Euclidean space when it was proposed, hence a new algorithm is invented to process RANN with the road network data. It is the first time that SRAT is defined and examined. A novel approach is proposed to answer this query. All queries have been tested with both synthetic and real-world data sets.