aggregate processing range in spatial databases

  • (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).

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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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  • CiteSeerX — Range Aggregate Processing in Spatial

    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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  • IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,

    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).

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  • Range aggregate processing in spatial databases CORE

    Range aggregate processing in spatial databases . By null Yufei Tao and D. Papadias. Cite . BibTex; Full citation; Publisher: Institute of Electrical and Electronics Engineers (IEEE) Year: 2004. DOI identifier: 10.1109/tkde.2004.93. OAI identifier: Provided by: MUCC (Crossref

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  • A Scalable Algorithm for Maximizing Range Sum in Spatial

    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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  • Indexing range sum queries in spatio-temporal databases

    4/1/2007· 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.

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  • Approximate range query processing in spatial network

    7/20/2012· Abstract. 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).

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  • Algorithms for Fundamental Spatial Aggregate Operations

    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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  • 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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  • Predicted range aggregate processing in spatio-temporal

    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 databases. Recent studies have

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  • Indexing range sum queries in spatio-temporal

    4/1/2007· 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.

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  • Efficient Maximum Range Search on Remote Spatial

    1/1/2013· 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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  • Clustering spatial networks for aggregate query processing

    been carried out on spatial databases to design effective storage schemes [16–23] for efficient query processing. These efforts can be categorized into two groups as proximity- and connectivity-based approaches. In the proximity-based approaches [16,19–21], interrelation of data is dependent on spatial proximity. However, query processing in spatial networks mostly involves route evaluation

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  • Algorithms for Fundamental Spatial Aggregate Operations

    queries, or box queries. Aggregate range queries perform some aggregate operation over spatial or spatiotemporal data that fall into a user speci ed area (the range or box), pos-sibly over some speci ed time window [17, 10, 13]. Such aggregation mechanisms seem to stem from the support for range queries provided by spatial indexing methods such as

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  • Approximate range query processing in spatial network

    7/20/2012· Abstract. 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).

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  • Supporting Spatial Aggregation in Sensor Network Databases

    proaches for aggregate processing in database systems, these works focus on efficient processing of the traditional aggre-gate operators. Literature on spatial databases also mainly focusonmodellingissues, theclassofnearestneighborqueries and index structures to provide fast answers to the queries [2].

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  • 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 results [ZMT+01, GAA03, ZTG02].

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  • Probabilistic Threshold Range Aggregate Query

    4/2/2009· 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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  • On Efficient Aggregate Nearest Neighbor Query Processing

    [25] Sharifzadeh M, Shahabi C, Kazemi L. Processing spatial skyline queries in both vector spaces and spatial network databases. ACM Transactions on Database Systems, 2009, 34(3): Article No. 14. [26] Qin L, Yu J X, Ding B, Ishikawa Y. Monitoring aggregate k-NN objects in road networks. In Proc. the 20th SSDBM, July 2008, pp.168-186.

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