• 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(PDF) Range aggregate processing in spatial databases,Range Aggregate Processing in Spatial Databases . Yufei Tao . Traditional research in spatial databases often aims at the range query, which retrieves the data . objects lying inside (or

  • 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-tree), which achievesIEEE 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

  • 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-temporalA 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

  • CiteSeerX — Predicted Range Aggregate Processing

    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) estimate methods, which utilizerange aggregate abstract a smartmods.pl,Range Aggregate Processing in Spatial Databases. We specialise in exposed aggregate which is ideal for outdoor areas. Add value to pool areas, driveways, pathways and alfresco areas with this durable and tactile finish. It comes in a wide range of finishes and colours that will suit all tastes.

  • Approximate range query processing in spatial

    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 search in network distanceIndexing range sum queries in spatio-temporal ,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.

  • Range Aggregate Processing in Spatial Databases

    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 queriesPredicted 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

  • 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. LongCiteSeerX — Citation Query Hierarchical cubes for ,Range Aggregate Processing in Spatial Databases by Yufei Tao, Dimitris Papadias TKDE,2004 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).

  • 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 approximatelyrange aggregate abstract a smartmods.pl,-range aggregate processing spatial databases-Abstract. In a range-aggegate query problem we wish to preprocess a set S of geometric objects such that given a query orthogonal range q, a certain intersection or proximity query on the objects of S intersected by q can be answered efficiently.

  • Probabilistic Threshold Range Aggregate Query

    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.Efficient Maximum Range Search on Remote Spatial ,2017-1-18 · processing either k-ANN queries or aggregate range queries on remote spatial databases. In other words, a new strategy for efficiently processing these queries is required. This paper applies Regular Polygon based Search Algorithm (RPSA)toefficiently searching approximate aggregate range

  • 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 forOn Efficient Aggregate Nearest Neighbor Query Processing,2015-2-1 · [2] Kolahdouzan M R, Shahabi C. Voronoi-based k nearest neighbor search for spatial network databases. In Proc. the 30th VLDB, Aug.31-Sept.3, 2004, pp.840-851. [3] Zhu L, Jing Y, Sun W, Mao D, Liu P. Voronoi-based aggregate nearest neighbor query processing in road networks.

  • 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. LongArticle: 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

  • Efficient Maximum Range Search on Remote Spatial

    2017-1-18 · processing either k-ANN queries or aggregate range queries on remote spatial databases. In other words, a new strategy for efficiently processing these queries is required. This paper applies Regular Polygon based Search Algorithm (RPSA)toefficiently searching approximate aggregate range 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

  • also aggregate data for query processing and the siz

    Range aggregate processing in spatial databases ResearchGate In this paper, we consider range count queries on multi-dimensional data points, where the result is the size of R (e.g., the number of hotels in an areaAggregate processing of multi-dimensional objects has also been studied theoretically, leading to several interesting resultsList 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

  • Range-aggregate query problems involving geometric

    Spatial Databases: A Tour. Prentice Hall. Google Scholar {13} SHERWANI, N. 1998. Algorithms for VLSI Physical Design Automation. Kluwer Academic. Google Scholar Digital Library {14} TAO, Y. AND PAPADIAS, D. 2004. Range aggregate processing in spatial databases. IEEE Transactions on Knowledge and Data Engineering 16, 12, 1555-1570.(PDF) Data Structures for Range-Aggregate Extent ,Data Structures for Range-Aggregate Extent Queries. 2008. Prosenjit Gupta. Download PDF. Download Full PDF Package. This paper. A short summary of this paper. 37 Full PDFs related to this paper. READ PAPER. Data Structures for Range-Aggregate Extent Queries. Download.

  • Query processing in spatial databases containing

    Despite the existence of obstacles in many database applications, traditional spatial query processing assumes that points in space are directly reachable and utilizes the Euclidean distance metric. In this paper, we study spatial queries in the presence of obstacles, where the obstructed distance between two points is defined as the length ofAggregation of Data by Using Top -K Spatial Query ,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. To our knowledge, there is no existing efficient solution for processing the top-k spatial preference