Spatial Keyword Search by using Point Regional QuadTree Algorithm

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
© 2017 by IJETT Journal
Volume-47 Number-4
Year of Publication : 2017
Authors : Ms Harshitha A.R, Smt. Christy Persya A
DOI :  10.14445/22315381/IJETT-V47P239


Ms Harshitha A.R, Smt. Christy Persya A "Spatial Keyword Search by using Point Regional QuadTree Algorithm", International Journal of Engineering Trends and Technology (IJETT), V47(4),236-242 May 2017. ISSN:2231-5381. published by seventh sense research group

Due to the current advances in geopositioning technologies and geo-location services, the amount of spatio-textual objects collected in numerous applications are quickly expanding. These spatio-textual items are collected from area based administrations and informal organizations, in which an item is described by its spatial location that is ?latitude? and ?longitude? and a set of keywords describing the items. Consequently, the study of spatial keyword search which explores both location and textual description of the objects has attracted great attention from the commercial organizations and research communities. In this paper, we mainly concentrate on fundamental problem in the spatial keyword search queries of the top k spatial keyword search method. In previous approaches, for extracting Top k result out of data in online business directory is not having efficiently relevance and faster result. In this paper, we are going to propose the method that will give the unique index structure, called point regional quadtree, which is carefully designed to exploit both spatial and keyword based pruning techniques to effectively reduce the search space. Given a set of spatio-textual objects, a query location and a set of query keywords, the generic model of the point regional quadtree retrieves the closest k objects each of which contains all keywords in the query. In this paper, how the proposed technique is used to calculate distance and direction for the nearest spatial objects is also discussed.


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Spatial, Keyword, Point Regional Quadtree, Spatial database, Indexing.