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range aggregate processing spatial databases

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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 multidimensional hyper-rectangle.In many scenarios (e.g., statistical analysis, data warehouses, etc.), however, users are interested only in summarized information about such objects, instead of their individual properties.

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

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).

range aggregate processing in spatial databases

range aggregate processing spatial databases 15349. Range Aggregate Processing in Spatial DatabasesRange Aggregate Processing in Spatial Databases Yufei Tao Department of Computer Science City University of Hong. Range aggregate processing in spatial databases – HKUST .

Range Aggregate Processing in Spatial Databases (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). This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP .

Range aggregate processing in spatial databasesHKUST

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 in Spatial Databases

Range Aggregate Processing in Spatial Databases Yufei Tao and Dimitris Papadias Abstract—A range aggregate query returns summarized information about the …

Range Aggregate Processing in Spatial Databases (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). This paper studies spatial indexes that solve such queries efficiently and proposes the aggregate Point-tree (aP .

Range Aggregate Processing in Spatial Databases

Range Aggregate Processing in Spatial Databases Yufei Tao and Dimitris Papadias Abstract—A range aggregate query returns summarized information about the …

Range aggregate processing in spatial databasesHKUST

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

Aggregate keyword routing in spatial database – … Due to the proliferation of Location-Based Service and popularity of online geo-tagged web pages, spatial keyword search has attracted significant attention from both academic and

Approximately processing aggregate range queries on

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.

Range aggregate processing in spatial databasesIEEE

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).

Approximately processing aggregate range queries on

Abstract. Processing aggregate range queries on remote spatial databases suffers from accessing huge and/or large number of databases that operate autonomously and …

aggregate processing sets

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 .

Supporting Spatial Aggregation in Sensor Network

Supporting Spatial Aggregation in Sensor Network . 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 . wireless sensor networks is orthogonal to our work on spatial aggregate processing. We can utilize any .

A Scalable Algorithm for Maximizing Range Sum in

A Scalable Algorithm for Maximizing Range Sum in Spatial Databases . require managing and processing a large amount of location information, and technologies studied in spatial databases . in spatial databases. The range aggregate (RA) query was proposed for the scenario where users are interested in sum-

range aggregate processing spatial databases

Range aggregate processing in spatial databases (PDF , Full-text (PDF) | A range aggregate query returns summarized information about the points falling in a …

Efficient Maximum Range Search on Remote Spatial

processing either k-ANN queries or aggregate range queries on remote spatial databases. In other words, a new In other words, a new strategy for efficiently processing these queries is required.

Probabilistic Threshold Range Aggregate Query Processing

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.

Clustering spatial networks for aggregate query processing

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.