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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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 - 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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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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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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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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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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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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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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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 ...
Read MoreCiteSeerX - 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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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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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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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 ...
Read More2017-6-30 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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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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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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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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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 ...
Read More2006-7-31 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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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
Read More2014-4-7 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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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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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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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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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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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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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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