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<p><b>Abstract</b>—A spatial distance join is a relatively new type of operation introduced for spatial and multimedia database applications. Additional requirements for ranking and stopping cardinality are often combined with the spatial distance join in online query processing or Internet search environments. These requirements pose new challenges as well as opportunities for more efficient processing of spatial distance join queries. In this paper, we first present an efficient <tmath>k{\hbox{-}}\rm distance</tmath> join algorithm that uses spatial indexes such as R-trees. Bidirectional node expansion and plane-sweeping techniques are used for fast pruning of distant pairs, and the plane-sweeping is further optimized by novel strategies for selecting a sweeping axis and direction. Furthermore, we propose adaptive multistage algorithms for <tmath>k{\hbox{-}}{\rm{distance}}</tmath> join and incremental distance join operations. Our performance study shows that the proposed adaptive multistage algorithms outperform previous work by up to an order of magnitude for both <tmath>k{\hbox{-}}{\rm{distance}}</tmath> join and incremental distance join queries, under various operational conditions.</p>
Spatial databases, k{\hbox{-}}{\rm{distance}} join, incremental distance join, adaptive query processing, multistage query processing, plane sweeping, sweeping index, estimating cutoff distance.

B. Moon, S. Lee and H. Shin, "Adaptive and Incremental Processing for Distance Join Queries," in IEEE Transactions on Knowledge & Data Engineering, vol. 15, no. , pp. 1561-1578, 2003.
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