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Aggregate nearest neighbor queries in spatial databases 1 jun 2005 , acm transactions on database systems tods tods homepage archive , conference on very large data bases, p802-813, september 09-12, 2003, , processing aggregate range queries on remote spatial databases,.Get Latest Price
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Range aggregate processing in spatial databases.By yufei tao and dimitris papadias.Abstracta range aggregate query returns summarized information about the points falling in a hyper-rectangle e., the total number of these points instead of their concrete ids.This paper studies spatial indexes that solve such queries.
A range aggregate query returns summarized information about the points falling in a hyper-rectangle e., the total number of these points instead of their concrete ids.This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate point-tree ap-tree, which achieves logarithmic cost to the data set.
Range aggregate processing spatial databases.Range aggregate processing spatial databas distributed and parallel databases,a adaptive processing of historical spatial range qu histogram and other aggregate.A scalable algorithm for maximizing range sum , a scalable algorithm for maximizing range sum in spatial , and technologies studied in.
Range aggregate processing in spatial databases.Citeseerx document details isaac councill, lee giles, pradeep teregowda abstracta range aggregate query returns summarized information about the points falling in a hyper-rectangle e., the total number of these points instead of their concrete ids.
Processing aggregate range queries on remote spatial databases suffers from accessing huge andor large number of databases that operate autonomously and simple andor restrictive web api interfaces.To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm rpsa to approximately search aggregate range query results over remote spatial.
Range aggregate processing in spatial databases.A range aggregate query returns summarized information about the points falling in a hyper-rectangle e., the total number of these points instead of their concrete ids.This studies spatial indexes that solve such queries efficiently and proposes the aggregate point-tree ap-tree, more.
Range aggregate processing in spatial databases by yufei tao, dimitris papadias - tkde , 2004 abstracta range aggregate query returns summarized information about the points falling in a hyper-rectangle e., the total number of these points instead of their concrete ids.
A scalable algorithm for maximizing range sum in spatial databases dong-wan choi1 chin-wan chung1,2 yufei tao2,3 1department of computer science, kaist, daejeon, korea 2division of web science and technology, kaist, daejeon, korea 3department of computer science and engineering, chinese university of hong kong, new territories, hong kong.
Predicted range aggregate processing in spatio-temporal databases wei liao, guifen tang, ning jing, zhinong zhong school of electronic science and engineering, national university of defense technology changsha, china liaoweinudtyahoo.Cn abstract predicted range aggregate pra query is an important researching issue in spatio-temporal.
Supporting aggregate range queries on remote spatial databases suffers from 1 huge andor large numbers of databases, and 2 limited type of access interfaces.This paper applies the regular polygon based search algorithm rpsa to effectively addressing these problems.
A probabilistic threshold range aggregate ptra query retrieves summarized information about the uncertain objects satisfying a range query, with respect to a given probability threshold.This paper is the first one to address this important type of query.
Let o be a set of objects a.Points in 2d space 2, where represents the real domain.Each object o o is associated with a positive value w o as its weight.Given non-negative values d 1 and d 2, the goal of the maximizing range sum maxrs problem is to place a d 1 d 2 rectangle r in 2 to maximize the covered weight of r, defined as.
The r-tree is known to be one of the most popular index structures to efficiently process window queries in spatial databases.Intuitively, the aggregate r-tree ar-tree , improves the r-trees performance in range sum queries by storing, in each intermediate entry, pre-aggregated sums of the objects in the subtree.1 shows an example of an ar-tree.
Our spatial aggregate operators are compatible with the aggregate processing of tag and easily portable to tinydb.In 9 introduce an architecture for sensor network monitoring.Their architecture benets from an energy-ecient aggregate processing for network properties digest functions.An average query is computed.
Spatial databases a tour.Google scholar 13 sherwani, n.Algorithms for vlsi physical design automation.Kluwer academic.Google scholar digital library 14 tao, y.And papadias, d.Range aggregate processing in spatial databases.Ieee transactions on knowledge and data engineering 16, 12, 1555-1570.
Publications of dimitris papadias.Ntaflos l, trimponias g, papadias d.A unified agent-based framework for constrained graph partitioning.Very large data bases journal vldbj, 282 221-241, 2019., papadopoulos, s.Engineering methods for differentially private histograms efficiency beyond utility.Ieee transactions on knowledge and data engineering.
Spatial database systems have been widely researched for more than past two decades.Published work related to spatial databases can broadly be classied as follows textbooks 97, 120, 84, 74 explain in detail about various topics in spatial databases such as logical data models for spatial data, algorithms for spatial operations, and.
Processing of timestamp queries and time interval queries 8,12,14,17, navigational queries 11, and nearest neighbor queries 6,13 in stdb, there has been little work on range sum queries for moving objects 15.Similar to multi-di-mensional databases such as olap on-line analytical processing systems, range sum queries are also crucial in.
Spatial databases accomplishments and research needs, s.Range aggregate processing in spatial databases, ieee transactions on knowledge and data engineering, vol.1555-1570, december, 2004.Haibo hu, dik lun lee.Range nearest-neighbor query, ieee transactions on knowledge and data engineering.
An efficient algorithm for processing top-k spatial preference queries.In relational databases, we rank tuples using an aggregate score function on their attribute values 2.For example, a real estate agency.Including spatial range queries, nearest neighbor queries, and spatial.
Yufei tao, jun zhang, dimitris papadias, nikos mamoulis an efficient cost model for optimization of nearest neighbor search in low and medium dimensional spaces.1610 1169-1184 2004 23 yufei tao, dimitris papadias range aggregate processing in spatial databases.
Particular attention is given to discussion of the efficient processing of spatial joins.Finally, chapter 8 provides an overview of current commercial solutions for handling of geographic information.The major contribution of this chapter is to relate the previously discussed theoretical study of spatial databases to existing commercial products.
Analyzing the performance of nosql vs.Sql databases for spatial and aggregate queries sarthak agarwala,, ks rajana ainternational institute of information technology hyderabad gachibowli, hyderabad, india abstract relational databases have been around for a long time and spatial databases have exploited this feature for close to two decades.
The range aggregate query on both non-spatial dimensions and spatial dimensions is a very important operation to support spatial olap.