range aggregate processing spatial databases
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(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
Range Aggregate Processing in Spatial Databases Yufei Tao Department of Computer Science City University of Hong Kong Tat Chee Avenue, Hong Kong [email protected] Dimitris Papadias
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[PDF] 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 spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP-tree), which achieves logarithmic cost to the data set cardinality (independently of the query size) for two-dimensional data.
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Range Aggregate Processing in Spatial Databases - CORE
We also present models that accurately predict the space consumption and query cost of the aP-tree and are therefore suitable for query optimization. Extensive experiments confirm that the proposed methods are efficient and practical. Index Terms—Database, spatial database, range queries, aggregation.
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CiteSeerX — Range Aggregate Processing in Spatial Databases
spatial database range aggregate processing logarithmic cost range aggregate query paper study spatial index data set cardinality range query query size space consumption query cost aggregate point-tree total number concrete id popular multiversion structural framework two-dimensional data extensive experiment small modification index term database present model
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Range aggregate processing in spatial databases - CORE
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-tree), which achieves logarithmic cost to the data set cardinality ( independently of the query size) for two-dimensional data.
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Aggregate Processing Spatial Databases
Citeseerx — Range Aggregate Processing In Spatial Databases. 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).
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A Scalable Algorithm for Maximizing Range Sum in
2017-6-30 We first review the range aggregate processing methods 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
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Yufei Tao's Publications - CUHK CSE
Range Aggregate Processing in Spatial Databases. IEEE Transactions on Knowledge and Data Engineering (TKDE), 16(12): 1555-1570, 2004. 2003 . Dimitris Papadias, Yufei Tao, Greg Fu, and Bernhard Seeger. An Optimal and Progressive Algorithm for Skyline Queries. Proceedings of ACM Conference on Management of Data (SIGMOD), pages 467-478, 2003. Long ...
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Indexing range sum queries in spatio-temporal databases ...
2007-4-1 Although spatio-temporal databases have received considerable attention recently, there has been little work on processing range sum queries on the
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Range Aggregate Processing in Spatial Databases - CORE
Range Aggregate Processing in Spatial Databases . By Yufei Tao and Dimitris Papadias. Abstract. 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 ...
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Range aggregate processing in spatial databases - CORE
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-tree), which achieves logarithmic cost to the data set ...
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Predicted range aggregate processing in spatio-temporal ...
2006-7-31 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 [email protected] Abstract Predicted range aggregate (PRA) query is an important researching issue in spatio-temporal
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Article: Approximately processing aggregate range queries ...
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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Efficient Maximum Range Search on Remote Spatial Databases ...
2013-1-1 Supporting aggregate range queries on remote spatial databases suffers from 1) huge and/or 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.
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Yufei Tao's Publications - CUHK CSE
Range Aggregate Processing in Spatial Databases. IEEE Transactions on Knowledge and Data Engineering (TKDE), 16(12): 1555-1570, 2004. 2003 . Dimitris Papadias, Yufei Tao, Greg Fu, and Bernhard Seeger. An Optimal and Progressive Algorithm for Skyline Queries. Proceedings of ACM Conference on Management of Data (SIGMOD), pages 467-478, 2003. Long ...
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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 Processing ...
2009-4-2 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.
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An Efficient Algorithm for processing Top-k Spatial ...
2019-7-1 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
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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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Article: Approximately processing aggregate range queries ...
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 More
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Yufei Tao's Publications - CUHK CSE
Range Aggregate Processing in Spatial Databases. IEEE Transactions on Knowledge and Data Engineering (TKDE), 16(12): 1555-1570, 2004. 2003 . Dimitris Papadias, Yufei Tao, Greg Fu, and Bernhard Seeger. An Optimal and Progressive Algorithm for Skyline Queries. Proceedings of ACM Conference on Management of Data (SIGMOD), pages 467-478, 2003. Long ...
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List of Papers and Books - Hui Xiong
2007-7-2 Spatial Databases: Accomplishments and Research Needs, S. Shekhar , S ... "Range Aggregate Processing in Spatial Databases," IEEE Transactions on Knowledge and Data Engineering, vol. 16, no. 12, pp. 1555-1570, December, 2004. Haibo Hu, Dik Lun Lee. "Range Nearest-Neighbor Query," IEEE Transactions on Knowledge and Data Engineering ...
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Algorithms for Fundamental Spatial Aggregate
2020-3-10 Aggregate operations have a long history of use and study in databases (see the survey [11]). The development of spa-tial aggregates is more recent, but has similarly received much attention. A signi cant portion of the literature on spatial aggregates is devoted to mechanisms to support range queries, or box queries. Aggregate range queries ...
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An Efficient Algorithm for processing Top-k Spatial ...
2019-7-1 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
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Supporting spatial aggregation in sensor network databases
Our spatial aggregate operators are compatible as the primary keys. with the aggregate processing of TAG and easily portable A set of different aggregation queries are now formally to TinyDB. definable on the the realized conceptual model of the sensor Zhao et al. in
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Range-aggregate query problems involving geometric ...
We consider variations of the standard orthogonal range searching motivated by applications in database querying and VLSI layout processing. In a generic instance of such a problem, called a range-...
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Top-K range-aggregate queries on categorical data ...
Efficient processing of top-K queries is a crucial requirement in many interactive applications that deals with huge amount of data. In particular efficient top-K processing has shown a great impact on performance in domains such as the web, text and data integration, business analytics, distributed aggregation of network logs and sensor data, data mining and so on.
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IJCST Vo l . 3, ISS ue 1, Spl . 5, Jan . - M 2012 ...
2012-4-20 H.2.4.h Query Processing, H.2.4.k Spatial Databases I. Introduction There is a growing interest in spatial data mining in many different areas such as transportation, ecology, epidemiology, etc. Many algorithms to extract knowledge from such data have been proposed in the literature. One of the main problems is
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Ranking Spatial Data by Quality Preferences Engineers ...
2017-1-12 Non-Spatial Ranking: Non-spatial ranking, which orders the objects by an aggregate function on their non-spatial values. Our top- k spatial preference query integrates these two types of ranking in an intuitive way. As indicated by our examples, this new query has a wide range of applications in service recommendation and decision support systems.
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