• M VINOTHKUMAR
• Dr K SELVAM

Reverse k Nearest Neighbor (RKNN) query is proposed based on the k Nearest Neighbor (KNN) query, which can be used to evaluate the influence of the query objects. At present RKNN query algorithms are mostly based on static or continuous objects, The algorithms for efficiently answering queries about large populations of moving objects are gaining interest. Given a group of nearby space objects as the query input, the authors propose the continuously monitoring RKNN algorithms based on the half-space pruning, compute the minimum bounding rectangles (MBRs) containing the query objects and consider the objects in the rectangles as a whole. Then, In order to get the query’s final RKNN results.

Half-space, Dominance, Metric Based, Probabilistic, Prune

"RKNN Using Clipping Methodologies", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 3, page no.2424-2430, March-2021, Available :http://www.jetir.org/papers/JETIR2103302.pdf

"RKNN Using Clipping Methodologies", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 3, page no. pp2424-2430, March-2021, Available at : http://www.jetir.org/papers/JETIR2103302.pdf