• (PDF) Range aggregate processing in spatial databases

    Range aggregate processing in spatial databases. January 2005; IEEE Transactions on Knowledge and Data Engineering 16(12):1555- 1570; DOI: 10.1109/TKDE.2004.93. Source; IEEE

    Range Aggregate Processing in Spatial Databases IEEE

    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 spati...

    Range aggregate processing in spatial databases IEEE

    01/11/2004· Range aggregate processing in spatial databases 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).

    range aggregate processing spatial databases

    range aggregate processing spatial databases. There are forty years of manufacturing history, with three major production bases,over 160 senior R&D engineers and 600+ large and medium-sized digital processing equipment, The first-line technicians and professional after-sales service personnel up to 2,300+ and 200+ respectively.

    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 Department of Computer Science Hong Kong University of Science and Technology Clear Water Bay, Hong Kong [email protected] Abstract A range aggregate query returns summarized information

    range aggregate processing spatial databases

    Range Aggregate Processing Spatial Databases. 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). Oline Chat . Service And Support . SpatialAggregation:

    range aggregate processing spatial databases

    We rst review the range aggregate processing methods in spatial databases the range aggregate ra query was proposed for the scenario where users are interested in summarized information about objects in a given range rather than individual objects thus, a ra query returns an aggregation value over objects qualied for a given range in

    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,

    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).

    range aggregate processing 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. range aggregate processing spatial databases . range

    range aggregate processing spatial databases

    range aggregate processing spatial databases. 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).

    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

    range aggregate processing spatial databases

    range aggregate processing spatial databases. Predicted Range Aggregate Processing in Spatiotemporal . CiteSeerX Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Predicted range aggregate (PRA) query is an important researching issue in spatiotemporal databases. Recent studies have developed two major classes of PRA query methods: (1) accurate approaches, which

    range aggregate processing spatial databases

    Range Aggregate Processing in Spatial Databases. Yufei Tao, Dimitris Papadias, "Range Aggregate Processing in Spatial Databases," IEEE Transactions on

    range aggregate processing spatial databases

    Range aggregate processing in spatial databases IEEE Xplore. A range aggregate query returns summarized information about the points falling in a hyperrectangle (e.g., the total number of these points instead of their concrete

    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

    range aggregate processing 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. range aggregate processing spatial databases . range

    range aggregate processing spatial databases

    range aggregate processing spatial databases. 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).

    Range Aggregate Processing Spatial Databases

    Range Aggregate Processing In Spatial Databases Henan. 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 . Details

    Aggregate Processing Spatial Databases BookZone

    range aggregate processing in spatial databases. range aggregate processing in spatial databases. aggregate for concrete; usa construction aggregate mill; list out aggregate production process; Get Price. Welcome to the SAX University of California, Riverside. SAX is the first symbolic representation for time series that allows for dimensionality reduction and indexing with a

    Indexing range sum queries in spatio-temporal databases

    01/04/2007· 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. Fig. 1 shows an example of an aR-tree.

    Range Aggregate Processing In Spatial Databases

    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 query results over remote spatial .

    range aggregate processing spatial databases

    Range aggregate processing in spatial databases IEEE Xplore. A range aggregate query returns summarized information about the points falling in a hyperrectangle (e.g., the total number of these points instead of their concrete

    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

    Approximately processing aggregate range queries on

    Approximately processing aggregate range queries on remote spatial databases January 2013 International Journal of Knowledge and Web Intelligence 4(4):314 335

    range aggregate processing in spatial da ases

    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 . Sales Online. definition of aggregate query processing

    Predicted Range Aggregate Processing in Spatio

    Predicted Range Aggregate Processing in Spatio-temporal Databases . By Wei Liao, Guifen Tang, Ning Jing and Zhinong Zhong. Abstract. 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

    CiteSeerX — Predicted Range Aggregate Processing in

    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 utilize

    Efficient Maximum Range Search on Remote Spatial

    01/01/2013· 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. This algorithm requests a series of k-NN queries to obtain approximate aggregate range query results. The query

    Indexing range sum queries in spatio-temporal databases

    01/04/2007· 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. Fig. 1 shows an example of an aR-tree.

    A Scalable Algorithm for Maximizing Range Sum in Spatial

    require managing and processing a large amount of location information, and technologies studied in spatial databases are getting a great deal of attention for this purpose. Tradi-tional researches in spatial databases, however, have mostly focused on retrieving objects (e.g., range search,nearest neighbor search,etc.), rather than nding the best location to optimize a certain objective

    Efficient Maximum Range Search on Remote Spatial

    01/01/2013· 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. This algorithm requests a series of k-NN queries to obtain approximate aggregate range query results. The query

    Efficient Maximum Range Search on Remote Spatial Databases

    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 query results. Assuming k-Nearest Neighbor (k-NN) queries [5],[6] are Web API interfaces available for

    A Scalable Algorithm for Maximizing Range Sum in Spatial

    require managing and processing a large amount of location information, and technologies studied in spatial databases are getting a great deal of attention for this purpose. Tradi-tional researches in spatial databases, however, have mostly focused on retrieving objects (e.g., range search,nearest neighbor search,etc.), rather than nding the best location to optimize a certain objective

    Approximate range query processing in spatial network

    Approximate range query processing in spatial network databases Haidar Al-Khalidi, Zainab Abbas, Maytham Hassan Safar Research output : Contribution to journal › Article › Research › peer-review

    Predicted Range Aggregate Processing In Spatio

    range aggregate processing spatial databases. 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). definition of aggregate query processing . aggregate query processing definition

    Approximate range query processing in spatial network

    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 distance

    also aggregate data for query processing and the size of

    Range Aggregate Processing in Spatial Databases Department of We also present models that accurately predict the space consumption and query cost of the Index Terms—Database, spatial database, range queries, aggregation. ж . degrades as the query size increases and eventually reaches. OррN=

    Aggregate nearest neighbor queries in spatial databases

    Given two spatial datasets P (e.g., 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 q 1,q n, an ANN query outputs the facility p ∈ P that minimizes the sum of distances |pq i for 1 ≤ i ≤ n that the users have to travel in order to meet

    Aggregate Analytic Window Query over Spatial Data

    dimensions, so the spatial aggregate analytic query is not easily supported. The spatial aggregate analytic query is meaningful and practical in the data analysis and visualization of spatial data. For example, show the total number of visits of POIs (point-of-interest) in each range (each range is defined by a fixed radius, and the centre of the range circle is each POI). In this paper, we

    Spatial database Wikipedia

    A spatial database is a database that is optimized for storing and querying data that represents objects defined in a geometric space. Most spatial databases allow the representation of simple geometric objects such as points, lines and polygons. Some spatial databases handle more complex structures such as 3D objects, topological coverages, linear networks, and TINs.

 

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