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About 7,044 papers for “Spatial query”

Spatial-Query-by-Sketch

M.J. Enenhofer · 2002

Today's methods for interacting with geographic information systems (GISs) and geographic databases are primarily aspatial, as they require users to deal with geographic data primarily through alphanumeric command languages. Spatial querying by typing a command in some spatial query language or by selecting the same syntax from pull-down menus is a tedious process, because it often requires extensive training in the use of the particular query language, and forces users to translate a spatial image they may have in their mind into a non-spatial language. To overcome this conceptual gap, we propose Spatial-Query-by-Sketch, a sketch-based GIS user interface that focuses on specifying spatial relations by drawing them. This query style more directly supports human spatial thinking, which is critical because users frequently have an image-like representation in their minds when they query about spatial configurations. This paper introduces the fundamental concepts of Spatial-Query-by-Sketch, provides examples of typical interactions and discusses query processing strategies by relaxing the constraints drawn in terms of a qualitative model.

Cited by 100

Spatial-Query-by-Sketch

Max J. Egenhofer · 1996

Today's methods for interacting with geographic information systems (GISs) and geographic databases are primarily aspatial, as they require users to deal with geographic data primarily through alphanumeric command languages. Spatial querying by typing a command in some spatial query language or by selecting the same syntax from pull-down menus is a tedious process, because it often requires extensive training in the use of the particular query language, and forces users to translate a spatial image they may have in their mind into a non-spatial language. To overcome this conceptual gap, we propose Spatial-Query-by-Sketch, a sketch-based GIS user interface that focuses on specifying spatial relations by drawing them. This query style supports more directly human spatial thinking, which is critical, because users frequently have an image-like representation in their minds when they query about spatial configurations. This paper introduces the fundamental concepts of Spatial-Query-bySketch, provides examples of typical interactions, and discusses query-processing strategies by relaxing the constraints drawn in terms of a qualitative model.

Cited by 0

Accelerating Spatial Query Operations

Frye, Roger · OpenSIUC (Southern Illinois University Carbondale) · 2025

Polygon overlay operations are used for various purposes such as GIS searches and queries, VLSI and basic geometric operations of intersection, union and difference. There have been recent research articles presenting algorithms using the GPU to perform line segment intersection for geometric operations. This paper presents two parallel algorithms implemented on the GPU that focus on the active list portion of the traditional serial plane sweep algorithm. The first algorithm uses a single block of threads to simulate the active list data structure in hardware; this algorithm is slow due to GPU thread block size limitations and synchronization points, but demonstrates favorable time complexity. The second algorithm uses dynamic parallelism to remove synchronization and scales to utilize available GPU hardware (single GPU). Experiments on both synthetic and real world data sets are performed. The results show improvement in execution time with respect to recent algorithms, and low memory usage compared to recent algorithms. Speedups of up to 38.8 over the serial sweep line algorithm on real world data are achieved.

Cited by 0

Continuous Spatial Query Processing

Jianzhong Qi, Rui Zhang, Christian S. Jensen et al. · ACM Computing Surveys · 2018

In the past decade, positioning system-enabled devices such as smartphones have become most prevalent. This functionality brings the increasing popularity of location-based services in business as well as daily applications such as navigation, targeted advertising, and location-based social networking. Continuous spatial queries serve as a building block for location-based services. As an example, an Uber driver may want to be kept aware of the nearest customers or service stations. Continuous spatial queries require updates to the query result as the query or data objects are moving. This poses challenges to the query efficiency, which is crucial to the user experience of a service. A large number of approaches address this efficiency issue using the concept of safe region . A safe region is a region within which arbitrary movement of an object leaves the query result unchanged. Such a region helps reduce the frequency of query result update and hence improves query efficiency. As a result, safe region-based approaches have been popular for processing various types of continuous spatial queries. Safe regions have interesting theoretical properties and are worth in-depth analysis. We provide a comparative study of safe region-based approaches. We describe how safe regions are computed for different types of continuous spatial queries, showing how they improve query efficiency. We compare the different safe region-based approaches and discuss possible further improvements.

Cited by 28Open access

SPATIAL LEARNED INDEX FOR ENHANCING SPATIAL QUERY

Galawizh M.Najeeb, Nzar A.Ali · Zenodo (CERN European Organization for Nuclear Research) · 2022

This work introduces and analyzes a novel approach to multi-dimensional indexing and machine learning, based on the concepts of the two data structure approaches Quad-tree and Hilbert curve. Using both traditional and learning strategies to obtain indexing for spatial data, execute nearest neighbor queries in both traditional and learning techniques (point, line, polygon spatial objects).An important result that goes beyond proposed algorithm (Spatial Learnt Index (SLI)), however is that the performance improvement over the Hilbert curve is greater than quad tree, by making comparison between them which is done through calculating execution time of each techniques for all three spatial objects types. Various evaluation criteria, mean square error (MSE), coefficient of determination (R2), were used to assess the performance of models.

Cited by 0Open access

Study on Fuzzy Spatial Location Model and Spatial Query Study on Fuzzy Spatial Location Model and Spatial Query

Yongjian Yang, Xiaohui Yang, Wei Zhang et al. · 2008

The spatial relationships plays an important role in GIS spatial data modeling, spatial query and spatial analysis etc. From the cognitive view, we represent and apply the information of relationships between spatial objects in the real world in computer system, study the fuzzy extension about description of spatial relationships at the base. Guided the spatial query the paper makes the model on the base of regular indefinite spatial inferring, puts fuzzy theory and spatial relationships theory into the spatial query practice. The paper found indefinite spatial inferring model based on the regular rules and embed it in space decision support system as the fuzzy spatial inference machine. It involves various spatial problems such as topology, orientation, base direction, naming distance, comparison distance, scale, shape and so on. Every aspect has made some progress, solves the fuzzy location and query problems in applying GIS and get better result in the experimental test.

Cited by 0

Spatial query processing for sketch-based query using heuristics

Lau Bee Theng, Wang Yin Chai · 2003

Sketching the spatial query is one of the leading spatial database query methods (Blaser (2000)) for searching similar configurations. However, when the sketched spatial scene is processed with ordinary query processing methods, it does not achieve the efficiency that is desired especially dealing with large datasets (N>1000). Therefore indexing and heuristics are proposed to be able to help in reducing the search space and enhance the search performance (Papadias and Mamoulis (1999)) for configuration similarity. The most prominent indexing method of spatial objects is the R-tree. With the indexed spatial objects, then heuristics can be applied to improve the searching efficiency i.e. reduce the searching cost and increase the number of solutions to the query. This paper aims to discuss the generic R-tree model, then discusses the heuristics that can be applied to utilize the data structure in the searching of configuration similarity in spatial query by sketch.

Cited by 2

Efficient Indexing of Spatial Query

Vikas Patil, Madhumati Unde, Manjusha Jagtap · 2015

Abstract- In past few years the Geographical Information Retrieval is very active field for research. Due to this research a new type of search engine came into existence called as Geographical Search Engine. Geographical search engine help to retrieve document which more textually and spatially relevant to our query. Indexing structure for spatial relevant is the main goal of this field and also to store and retrieve document having spatial scope of the given query. In this context we give an efficient tree structure called IR-tree, which allows searches to adopt different scope on textual and spatial relevance of document.

Cited by 0

CONTENT-BASED SPATIAL QUERY RETRIEVAL

Lau Bee Theng, Yanbing Wang · Journal of IT in Asia · 2016

Information acquisition with the availability of modern information technology has become easier. We rely on various information systems in our daily lives. Geographical information system and spatial query retrieval become more and more important in vehicle navigation, robot automation, and satellite signal processing. Spatial query is made easy with the handheld technology like PDA and sketching device. However powerful query methodology needs powerful retrieval techniques to produce the desired output. Content based spatial query retrieval is one of the best resorts for spatial query retrieval. Structural spatial query retrieval is in content based retrieval family that is also an active research area in spatial databases. Structural spatial query retrieval assesses similarity by its structural arrangement, known as configuration similarity. This research developed an enhanced structural spatial query retrieval model for spatial databases.

Cited by 0Open access

Query Processing in Spatial Databases

Antonio Corral, Michael Vassilakopoulos · IGI Global eBooks · 2005

Spatial data management has been an active area of intensive research for more than two decades. In order to support spatial objects in a database system, several important issues must be taken into account such as spatial data models, indexing mechanisms, and efficient query processing. A spatial database system (SDBS) is a database system that offers spatial data types in its data model and query language and supports spatial data types in its implementation, providing at least spatial indexing and efficient spatial query processing (Güting, 1994).

Cited by 5

Query Processing in Spatial Databases

Antonio Corral, Michael Vassilakopoulos · IGI Global eBooks · 2011

Spatial data management has been an active area of intensive research for more than two decades. In order to support spatial objects in a database system, several important issues must be taken into account such as spatial data models, indexing mechanisms, and efficient query processing. A spatial database system (SDBS) is a database system that offers spatial data types in its data model and query language and supports spatial data types in its implementation, providing at least spatial indexing and efficient spatial query processing (Güting, 1994). Request access from your librarian to read this chapter's full text.

Cited by 0

Efficient Location Aware Spatial Query

Lin, Qianlu · UNSWorks (University of New South Wales, Sydney, Australia) · 2013

With the emergence of location-aware mobile device technologies, communication technologies and GPS systems, location-aware queries have attracted great attentions in many important applications such as location based service (LBS) and geographic information system (GIS). The location-aware query has many different types such as k nearest neighbors(kNN), reverse nearest neighbor (RNN), top-k preference query, and skyline set. The spatial database can usually be categorized as certain data and uncertain data. There is a special spatial database, termed spatial database associated with facility types. In this thesis, we focus on investigating the location-aware queries on this special database. In user recommendation web services, the facility types can be supermarkets, pubs, public transport stations, etc. The location-aware queries include top-k preference query and spatial skyline operators. We first study the top-k preference query on the proposed spatial database. We study the problem of finding the most accessible locations among a set of possible sites. We propose two algorithms, named separate-tree and one-tree to efficiently perform top-k preference query. We then study the spatial skyline operators on the proposed spatial database. First, we formularize the skyline operators on the proposed spatial database. Then we propose P-GSSKY algorithm that can significantly reduce the number of non-promising objects in the computation, and J-GSSKY that can compute GSSKY efficiently in terms of I/O cost. We further study the nearest neighbor search and all nearest neighbor search problem in spatial database. We propose a new data structure, termed AVR-tree which intergrates voronoi diagrams to the R-tree structure in order to effectively prune unpromising objects in the highlevel of R-tree. Last, we study the range search and k nearest neighbor search on uncertain data. We propose a novel index structure, called U-Quadtree, to effectively organize the multi-dimensional uncertain objects with arbitrary probability distribution functions (pdf). Algorithms for performing range search and k nearest neighbor search are provided. Then we provide a cost model and propose efficient optimal U-Quadtree construction algorithm.

Cited by 0Open access

Spatial Query Optimization With Learning

Xin Zhang, Ahmed Eldawy · Proceedings of the VLDB Endowment · 2024

Query optimization is a key component in database management systems (DBMS) and distributed data processing platforms. Recent research in the database community incorporated techniques from artificial intelligence to enhance query optimization. Various learning models have been extended and applied to the query optimization tasks, including query execution plan, query rewriting, and cost estimation. The tasks involved in query optimization differ based on the type of data being processed, such as relational data or spatial geometries. This tutorial reviews recent learning-based approaches for spatial query optimization tasks. We go over methods designed specifically for spatial data, as well as solutions proposed for high-dimensional data. Additionally, we present learning-based spatial indexing and spatial partitioning methods, which are also vital components in spatial data processing. We also identify several open research problems in these fields.

Cited by 2

Skyline Micro-Cluster Query: A Novel and Practical Spatial Query

Jing Lu, Yuhai Zhao, Zhengkui Wang et al. · 2023

This paper presents a novel spatial query, skyline micro-cluster (SMC) query. Given a set of data points P, a query point q, a radius γ and a density parameter k, the SMC query returns the skyline micro-clusters (MCs), where MC is a set of points in P that can be covered by a circle with radius γ and the number of points in MC is at least k. In this paper, we formally define the SMC query. As the brute-force approach to solving the SMC query in massive datasets has high computation and memory costs, we propose a basic skyline micro-cluster query algorithm, BSMC, which can reduce the time complexity from O(2<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</sup>) to O(N<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup>). Furthermore, on top of BSMC, we propose an efficient skyline micro-cluster query algorithm (ESMC). In ESMC, we use the z-value index and propose a filter to remove the invalid micro-clusters, which reduces significant computation overhead. To reduce the memory overhead, we propose an incremental skyline query method. A comprehensive performance study is conducted on real datasets and the experimental results show that our proposed method, ESMC, can significantly improve the SMC query performance.

Cited by 0

Query Compilation based Distributed Morsel-driven Parallel Spatial Query Processing

Rahul Sahni, Xiaozheng Zhang, Sudip Chatterjee et al. · 2024

Driven by the need to support spatial data applications, most relational databases offer spatial SQL query features. However, traditional relational databases are not scalable, and their query processing follows a pull-based tuple-at-a-time model, which is not efficient for large data volumes. Although several specialized spatial data processing systems were developed by extending frameworks, such as Spark and Hadoop, these systems offer limited or no support for spatial SQL query execution. The few systems that support SQL querying, suffer from the overheads of the pull-based model.

Cited by 1