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range aggregate processing in spatial databases

(PDF) Range aggregate processing in spatial databases

Traditional research in spatial databases often aims at the range query, which retrieves the data objects lying inside (or intersecting) a multi-dimensional hyper-rectangle. In many scenarios (e.g.,

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Range Aggregate Processing in Spatial Databases

A range aggregate query returns summarized information about the points falling in a hyper- rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies

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CiteSeerX — Range Aggregate Processing in Spatial

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract—A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., 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

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA

2005-3-25  Range Aggregate Processing in Spatial Databases Yufei Tao and Dimitris Papadias Abstract—A range aggregate query returns summarized information about the points falling in a hyper-rectangle (e.g., the total number of these points instead of their concrete ids). This paper studies spatial indexes that solve such queries efficiently and

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Predicted Range Aggregate Processing in Spatio-temporal

A high dynamic range camera provides the processing unit with image data. Measurement points of lane borders, calculated by a robust edge detection algorithm, are

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Predicted Range Aggregate Processing in Spatio-temporal

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Predicted range aggregate (PRA) query is an important researching issue in spatio-temporal databases. Recent studies have developed two major classes of PRA query methods: (1) accurate approaches, which search the common moving objects indexes to obtain an accurate result; and (2)

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Approximate range query processing in spatial network

2012-7-20  Spatial range query is one of the most common queries in spatial databases, where a user invokes a query to find all the surrounding interest objects. Most studies in range search consider Euclidean distances to retrieve the result in low cost, but with poor accuracy (i.e., Euclidean distance less than or equal network distance). Thus, researchers show that range

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Approximate range query processing in spatial network

spatial road network and approximate search. 2.1 Range search in spatial road network. Range search is one of the most common types of queries. in

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Moving Range Query Processing in Spatial Databases

First, we introduce a new “approximate moving range query” to optimise the query process in two ways: i) we reduce the amount of time needed to obtain the results; and ii) we give the users ...

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A Scalable Algorithm for Maximizing Range Sum in

2017-6-30  in spatial databases. The range aggregate (RA) query was proposed for the scenario where users are interested in sum-marized information about objects in a given range rather than individual objects. Thus, a RA query returns an ag-gregation value over objects qualified for a given range. In order to efficiently process RA queries, usually ...

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Predicted Range Aggregate Processing in Spatio-temporal

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Predicted range aggregate (PRA) query is an important researching issue in spatio-temporal databases. Recent studies have developed two major classes of PRA query methods: (1) accurate approaches, which search the common moving objects indexes to obtain an accurate result; and (2)

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Predicted range aggregate processing in spatio

2006-7-31  We start with a concrete definition of aggregate query in spatio-temporal databases before presenting the PRA-tree index. By definition, a spatiotemporal object is a unified object with spatial and temporal extent [2]. A pure spatial object can be a point, a line, or a region in two or three-dimensional space. The position and/or shape either

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Approximately processing aggregate range queries on

2013-1-1  Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or 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

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Article: Approximately processing aggregate range

2014-4-7  Abstract: Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces. To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm (RPSA) to approximately ...

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A Scalable Algorithm for Maximizing Range Sum in

2017-6-30  in spatial databases. The range aggregate (RA) query was proposed for the scenario where users are interested in sum-marized information about objects in a given range rather than individual objects. Thus, a RA query returns an ag-gregation value over objects qualified for a given range. In order to efficiently process RA queries, usually ...

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Indexing range sum queries in spatio-temporal databases

2007-4-1  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-tree’s performance in range sum queries by storing, in each intermediate entry, pre-aggregated sums of the objects in the subtree. Fig. 1 shows an example of an aR-tree.

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Probabilistic Threshold Range Aggregate Query

2009-4-2  Large amount of uncertain data is inherent in many novel and important applications such as sensor data analysis and mobile data management. 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.

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dataunion

dataunion

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Supporting Spatial Aggregation in Sensor Network

2016-5-21  network processing of the aggregation queries on the data generated in the sensor network. We use the ad-hoc query routing algorithm of TAG to disseminate our query into the network. Our spatial aggregate operators are compatible with the aggregate processing of TAG and easily portable to TinyDB. Zhao et al. in [9] introduce an architecture for ...

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Rectangle-efficient aggregation in spatial data streams

2012-5-21  Rectangles are a basic primitive object in spatial databases, and efficient aggregation of rectangles is a fundamental task. ... Range aggregate processing in spatial databases. IEEE TKDE, 16(12):1555--1570, 2004. Google Scholar Digital Library; Nitin Thaper, Sudipto Guha, Piotr Indyk, and Nick Koudas. Dynamic multidimensional histograms. In ...

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Predicted range aggregate processing in spatio

2006-7-31  We start with a concrete definition of aggregate query in spatio-temporal databases before presenting the PRA-tree index. By definition, a spatiotemporal object is a unified object with spatial and temporal extent [2]. A pure spatial object can be a point, a line, or a region in two or three-dimensional space. The position and/or shape either

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PDF - Query processing in spatial network databases

2003-9-8  Abstract: Given two spatial datasets P (eg, facilities) and Q (queries), an aggregate nearest neighbor (ANN) query retrieves the point(s) of P with the smallest aggregate distance(s) to points in Q Assuming, for example, n users at locations q1,qn, an ANN query outputs the facility p ∈ P that minimizes the sum of distances vpqiv for 1 ≤ i ≤ n that the users have to

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Article: Approximately processing aggregate range

2014-4-7  Abstract: Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and simple and/or restrictive web API interfaces. To overcome these difficulties, this paper applies a revised version of regular polygon-based search algorithm (RPSA) to approximately ...

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dataunion

dataunion

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Clustering spatial networks for aggregate query

2021-3-22  models, spatial access methods, and query processing techniques are proposed [1,2] to overcome the problems faced within the extensive scale of geo-graphic information systems (GIS). The increasing demand on geographic applications made spatial databases quite popular. The research on spatial databases focused on the Euclidean space, where the

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Materialized views for count aggregates of spatial data

title = "Materialized views for count aggregates of spatial data", abstract = "We address the problem of efficient processing of count aggregate queries for spatial objects in OLAP systems. One of the main issues affecting the efficient spatial analysis is the, so called, distinct counting problem. The core of the problem is due to the fact ...

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On efficient mutual nearest neighbor query processing in

2009-8-1  This paper studies a new form of nearest neighbor (NN) queries, namely mutual nearest neighbor (MNN) search. Given a dataset D, a query point q, and two parameters k1 and k2, an MNN query retrieves those objects p ∈ D such that p ∈ NNk1 ( q) 1 and q ∈ NNk2 ( p ), i.e., it requires each answer object2 to be one of the k1 nearest neighbors ...

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Redundancy in Spatial Databases - BU

2000-9-7  spatial objects involved in overlap queries [OREN86a, OREN86bl. Each spatial object in each input set is transformed to a set of l-d intervals. An algorithm called spatial join implements the filter step. Each resulting candidate is a pair of objects, one from each input file. that are

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Monitoring best region in spatial data streams in road

Abstract Given a set of spatial objects O, the search radius r and the submodular function f are specified by the user. The best region search (BRS) is to find an optimal area with fixed range size... Abstract Given a set of spatial objects O, the search radius r and the submodular function f are specified by the user. The best region search ...

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Clustering spatial networks for aggregate query

2008-3-1  In spatial networks, clustering adjacent data to disk pages is highly likely to reduce the number of disk page accesses made by the aggregate network operations during query processing. For this purpose, different techniques based on the clustering graph model are proposed in the literature.

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