Modeling and querying fuzzy spatiotemporal databases

Sözer, Aziz; Yazıcı, Adnan; Oğuztüzün, Halit; Taş, Osman

doi:10.1016/j.ins.2008.05.034

Cited by 56 publications

(23 citation statements)

References 41 publications

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“…Spatio-temporal objects are not always crisp, but fuzzy and uncertain in the real world [11]. In order to deal with the fuzziness and imprecision of spatio-temporal objects, several efforts have been made to model fuzzy spatio-temporal objects and their topological relationships, such as fuzzy set theory-based methods [15], [16], rough set theory-based method [17], point-set topology [13], motion-based approaches [14], [18], [19], and dimensional-extended method [20], [21].…”

Section: Fuzzy Spatio-temporal Objects and Their Topological Relationmentioning

confidence: 99%

“…Spatial topological relations play a significant role in Geographic Information System and spatial database, whose purpose is to describe relationships between crisp spatial objects [11]. Randell et al [27] propose the Region Connection Calculus (short for RCC) theory in the field of spatial domain knowledge.…”

Section: Spatial Topological Relationsmentioning

confidence: 99%

“…All the approaches are based on the assumption that spatio-temporal objects have crisp boundaries and their positions can be accurately measured. In fact, in the real world, spatio-temporal objects are not always crisp but with the nature of fuzziness and imprecision [11]. When spatio-temporal objects are fuzzy, the issue of fuzzy topological relationships emerges [12].…”

Section: Introductionmentioning

confidence: 99%

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Modeling Topological Relationships between Fuzzy Spatio-Temporal Objects

Cheng

Zhang

2016

CIT. J. comput. inf. technol

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Topological relationships between spatio-temporal objects are the most fundamental elements in spatio-temporal database systems, GIS, and image database systems. The research issue of modeling topological relationships has increasingly attracted attention, especially for querying of spatio-temporal objects and reasoning of topological relationships. Currently, topological relationship operating on spatio-temporal objects with precisely defined boundaries has been well studied. However, in the real world, spatio-temporal objects are not always crisp but with the nature of fuzziness and imprecision. Therefore, how to model topological relationship between fuzzy spatio-temporal objects is a significant topic and needs more investigations. This paper presents a study on modeling topological relationships between fuzzy spatio-temporal objects. Firstly, we give a model of fuzzy spatio-temporal objects in three-dimensional space and define those objects as moving fuzzy points, moving fuzzy lines, and moving fuzzy regions. On this basis, we propose a model for identifying basic topological relations between fuzzy spatio-temporal objects. Furthermore, in order to describe the evolution of basic topological relations over time, we give a model of complex topological relationships which are the sequences of basic relationships. The benefit of this model is that the complex topological relationships can be used as fuzzy spatio-temporal query operators in query languages. Finally, we provide some query examples to demonstrate fuzzy spatio-temporal queries in spatio-temporal database. ACM CCS (2012) Classification

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Section: Fuzzy Spatio-temporal Objects and Their Topological Relationmentioning

confidence: 99%

Section: Spatial Topological Relationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modeling Topological Relationships between Fuzzy Spatio-Temporal Objects

Cheng

Zhang

2016

CIT. J. comput. inf. technol

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“…In real world application, however, information are defined abstractly or fuzzily [10]. Different kind of imperfect information adheres to the geospatial information have been studied in literature [11].…”

Section: Related Workmentioning

confidence: 99%

Framework for Spatial Query Resolution for Decision Support Using Geospatial Service Chaining and Fuzzy Reasoning

Mukherjee

Ghosh

2011

Information Intelligence, Systems, Technology and Management

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Abstract. Geospatial data play a vital role in various decision making systems. Technological advancements have enabled users to access geospatial functionalities as services over web. In many decision support systems, it is required that more than one service is to be involved to help decision makers, calling for a service chaining. Chaining distributed geospatial services requires dealing with several heterogeneity issues such as semantic, syntactic issues. In addition, properties of geospatial data are fuzzy by nature. The fuzziness may exist in thematic definition and in spatial properties. This may lead to inflexible, less accurate decision making. Thus, to avail more accurate decision making, the uncertainty associated with the spatial information should be captured. In this paper, an approach for service chaining in decision support systems has been taken, along with fuzzy logic to resolve user queries and process imprecise information. Service chaining has been used for integrating distributed geospatial services, and fuzzy logic has been incorporated with services to capture fuzziness and uncertainty that are intrinsic to the data.

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“…Spatiotemporal data is characterized by both spatial [3] and temporal [4] semantics. With the development of spatiotemporal data, some operations based on spatiotemporal data are researched, such as spatiotemporal data query [5] and spatiotemporal data indexing [6].…”

Section: Introductionmentioning

confidence: 99%

Querying Spatiotemporal Data Based on XML Twig Pattern

Bai¹,

Li²,

Liu³

2016

JSW

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Abstract:With the increasing applications based on location, researches on spatiotemporal data, especially queries of spatiotemporal data have attracted a lot of attention. XML, as a standard language of information exchanging over the Web, has the ability to query spatiotemporal data. In this paper, we propose an algorithm, TwigStackSP, for matching a spatiotemporal XML query twig pattern. We represent spatiotemporal data by adding spatial and temporal attributes in general data and extend region coding scheme to filter the nodes in P-C relationship. Our technique uses a chain of linked stacks to compactly represent partial results to root-to-leaf query paths, which are then composed to obtain matches for the twig pattern. It can be proved that TwigStackSP is I/O and CPU optimal when there are no text nodes in P-C relationship of twig pattern.

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Modeling and querying fuzzy spatiotemporal databases

Cited by 56 publications

References 41 publications

Modeling Topological Relationships between Fuzzy Spatio-Temporal Objects

Modeling Topological Relationships between Fuzzy Spatio-Temporal Objects

Framework for Spatial Query Resolution for Decision Support Using Geospatial Service Chaining and Fuzzy Reasoning

Querying Spatiotemporal Data Based on XML Twig Pattern

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