
Design an Efficient Top-K Query Retrieval Technique for GIQ problems
Author(s) -
V. Kumaresan,
S. Vairachilai
Publication year - 2015
Publication title -
journal of advance research in computer science and enigneering
Language(s) - English
Resource type - Journals
ISSN - 2456-3552
DOI - 10.53555/nncse.v2i5.446
Subject(s) - intersection (aeronautics) , query optimization , computer science , set (abstract data type) , range (aeronautics) , point (geometry) , integer (computer science) , process (computing) , query expansion , space (punctuation) , sargable , query language , theoretical computer science , algorithm , web search query , mathematics , search engine , information retrieval , materials science , geometry , engineering , composite material , programming language , aerospace engineering , operating system
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. In our proposed system we are going to perform multiple query processing. Because in the existing approach it can able to process only one query at the time. But in our proposed work we process multiple queries at the time.