Spatial Information Retrieval in Digital Ecosystems

Carniel, Anderson Chaves

doi:10.1145/3415958.3433038

Cited by 5 publications

(7 citation statements)

References 42 publications

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“…Spatial information retrieval is a common task required by advanced applications [Carniel 2020], such as location-based services, smart cities, and mobile recommendation systems. The goal of such applications is to enrich the data analysis by taking into the importance of "where".…”

Section: Introductionmentioning

confidence: 99%

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The Application of Spatial Approximations to Spatial Query Processing: A Systematic Review of Literature

Bertella

Lopes

Oliveira

et al. 2021

Anais Do XXXVI Simpósio Brasileiro De Banco De Dados (SBBD 2021)

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Spatial approximations simplify the geometric shape of complex spatial objects. Hence, they have been employed to alleviate the evaluation of costly computational geometric algorithms when processing spatial queries. For instance, spatial index structures employ them to organize spatial objects in tree structures (e.g., the R-tree). We report experiments considering two real datasets composed of ∼1.5 million regions and ∼2.7 million lines. The experiments confirm the performance benefits of spatial approximations and spatial index structures. However, we also identify that a second processing step is needed to deliver the final answer and often requires higher processing time than the step that uses index structures only. It leads to the interest in studying how spatial approximations can be efficiently used to improve both steps. This paper presents a systematic review on this topic. As a result, we provide an overview and comparison of existing approaches that propose, evaluate, or make use of spatial approximations to optimize the performance of spatial queries. Further, we characterize them and discuss some future trends.

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Section: Introductionmentioning

confidence: 99%

“…Spatial relationships, such as topological relationships (e.g., overlaps, contains) [Schneider and Behr 2006], are often employed as conditions in spatial queries. Thus, several types of spatial queries have been defined in the literature (see [Carniel 2020] for a survey).…”

Section: Introductionmentioning

confidence: 99%

The Application of Spatial Approximations to Spatial Query Processing: A Systematic Review of Literature

Bertella

Lopes

Oliveira

et al. 2021

Anais Do XXXVI Simpósio Brasileiro De Banco De Dados (SBBD 2021)

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“…As a basic feature, spatial database systems and GIS allow users to pose different types of spatial queries [Gaede and Günther 1998;Carniel 2020]. Examples are depicted in Figure 1.…”

Section: Spatial Data Types and Spatial Query Processingmentioning

confidence: 99%

“…For instance, the k-nearest neighbor query (kNN) finds a set of spatial objects that are the k-nearest neighbors of the search object (Figure 1f). Other types of spatial queries can be derived, as discussed in [Gaede and Günther 1998;Carniel 2020]. Some types of spatial queries can be directly answered by using spatial approximations only, such as the CQ (Figure 1c).…”

Section: Spatial Data Types and Spatial Query Processingmentioning

confidence: 99%

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A Systematic Review of Spatial Approximations in Spatial Database Systems

Bertella

Lopes

Oliveira

et al. 2022

jidm

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Many applications rely on spatial information retrieval, which involves costly computational geometric algorithms to process spatial queries. Spatial approximations simplify the geometric shape of complex spatial objects, allowing faster spatial queries at the expense of result accuracy. In this sense, spatial approximations have been employed to efficiently reduce the number of objects under consideration, followed by a refinement step to restore accuracy. For instance, spatial index structures employ spatial approximations to organize spatial objects in hierarchical structures (e.g., the R-tree). It leads to the interest in studying how spatial approximations can be efficiently employed to improve spatial query processing. This article presents a systematic review on this topic. We gather relevant studies by performing a search string on several digital libraries. We further expand the studies under consideration by employing a single iteration of the snowballing approach, where we track the reference list of selected papers. As a result, we provide an overview and comparison of existing approaches that propose, evaluate, or make use of spatial approximations to optimize the performance of spatial queries. The spatial approximations mentioned by the approaches are also summarized. Further, we characterize the approaches and discuss some future trends.

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Defining and designing spatial queries: the role of spatial relationships

Carniel

2023

Geo-spatial Information Science

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Spatial Information Retrieval in Digital Ecosystems

Cited by 5 publications

References 42 publications

The Application of Spatial Approximations to Spatial Query Processing: A Systematic Review of Literature

The Application of Spatial Approximations to Spatial Query Processing: A Systematic Review of Literature

A Systematic Review of Spatial Approximations in Spatial Database Systems

Defining and designing spatial queries: the role of spatial relationships

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