Description

In a given geometric objects, set of objects are retrieved as results for the given query. The problem is defined as geometric query intersection problem. The problem defines that, for the given user query, all the relevant results which are intersected by the query are showed as output. Because of the large number results, it occupies the huge memory space. For that here we propose a solution that we show the top-k results as the output where k is the integer. This paper gives a general technique to solve any top-k GIQ problem efficiently. The technique relies only on the availability of an efficient solution for the underlying (non-top-k) GIQ problem, which is often the case. Using this, asymptotically efficient solutions are derived for several top-k GIQ problems, including top-k orthogonal and circular range search, point enclosure search, half space range search, etc. Implementations of some of these solutions, using practical data structures, show that they are quite efficient in practice. This paper also does a formal investigation of the hardness of the top-k GIQ problem, which reveals interesting connections between the top-k GIQ problem and the underlying (non-top-k) GIQ problem. The system report on some experiments conducted with practical versions of the top-k orthogonal range search and top-k orthogonal point enclosure search algorithms discussed. our implementations use R-trees [6] instead of the asymptotically efficient counting and reporting structures described i. Rtrees are well known in the database literature for answering orthogonal range search and orthogonal point enclosure search efficiently.