Spatial Keyword Search by using Point Regional QuadTree Algorithm
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International Journal of Engineering Trends and Technology (IJETT) | 
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| © 2017 by IJETT Journal | ||
| Volume-47 Number-4 |
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| Year of Publication : 2017 | ||
| Authors : Ms Harshitha A.R, Smt. Christy Persya A |
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| DOI : 10.14445/22315381/IJETT-V47P239 |
Citation
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. www.ijettjournal.org. published by seventh sense research group
Abstract
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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Keywords
Spatial, Keyword, Point Regional
Quadtree, Spatial database, Indexing.