The Experts below are selected from a list of 57831 Experts worldwide ranked by ideXlab platform
Christophe Claramunt - One of the best experts on this subject based on the ideXlab platform.
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modeling trajectories a spatio Temporal Data Type approach
Database and Expert Systems Applications, 2009Co-Authors: Ali Frihida, Donia Zheni, Henda Ben Ghezala, Christophe ClaramuntAbstract:Retrieving and analyzing trajectories favor the study of human behaviors in space and time. Although Time Geography has long proposed a conceptual framework for the interpretation of trajectory Data, there is still a need for Database and semantic models that support representation and manipulation. In fact, the concept of trajectory is rarely addressed as a sui generis Data Type that can be embedded in a Database structure. This paper introduces an algebraic Spatio-Temporal Trajectory Data Type (STT) for the representation of object trajectory. The STT is an abstract Data Type endowed with a set of operations designed as a way to cover the syntax and semantics of a given trajectory. It is considered as a Data structure that can be used for the design and implementation of spatio-Temporal Databases.
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DEXA Workshops - Modeling Trajectories: A Spatio-Temporal Data Type Approach
2009 20th International Workshop on Database and Expert Systems Application, 2009Co-Authors: Ali Frihida, Donia Zheni, Henda Ben Ghezala, Christophe ClaramuntAbstract:Retrieving and analyzing trajectories favor the study of human behaviors in space and time. Although Time Geography has long proposed a conceptual framework for the interpretation of trajectory Data, there is still a need for Database and semantic models that support representation and manipulation. In fact, the concept of trajectory is rarely addressed as a sui generis Data Type that can be embedded in a Database structure. This paper introduces an algebraic Spatio-Temporal Trajectory Data Type (STT) for the representation of object trajectory. The STT is an abstract Data Type endowed with a set of operations designed as a way to cover the syntax and semantics of a given trajectory. It is considered as a Data structure that can be used for the design and implementation of spatio-Temporal Databases.
Mirta Baranović - One of the best experts on this subject based on the ideXlab platform.
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MIPRO - Managing moving objects in the context of spatio-Temporal Data streams
2011Co-Authors: Emir Meskovic, Zdravko Galić, Mirta BaranovićAbstract:Managing moving objects in DSMS has recently been a focus of a relatively intense research. In this paper, we are concerned with Data streams containing a location of a moving object at any time instant. Instead of using spatial and time instant Data Types separately, for representing spatio-Temporal characteristics of Data streams, we propose a unified approach based on specialized Temporal Data Type constructor. This Type constructor, parameterized with a spatial Type representing objects location, yields a corresponding Type whose values are pairs, consisting of an instant of time and a value of spatial Type. With this approach, it is possible to represent Temporal development of an objects' location within one time interval by using two consecutive values of this Temporal Data Type. Since moving object is basically obtained just by assembling these Temporal developments whose time intervals are disjoint, we also propose an approach for extracting moving objects out of spatio-Temporal Data streams based on user-defined aggregate functions (UDAF) over spatio-Temporal Data Types. With this approach, it is possible to manage moving objects encapsulated within spatio-Temporal Data streams using SQL-like query language.
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Mobile Data Management (2) - Managing Moving Objects in Spatio-Temporal Data Streams
2011 IEEE 12th International Conference on Mobile Data Management, 2011Co-Authors: Emir Meskovic, Zdravko Galić, Mirta BaranovićAbstract:Managing moving objects in DSMS has been a focus of a relatively intense research in recent years. In this paper, we are concerned with Data stream tuples containing a location of a moving object at any time instant. Instead of using spatial and time instant Data Types separately, for representing spatio-Temporal component in such Data streams, we propose a use of a specialized Temporal Data Type constructor. This Type constructor parameterized with a spatial Type representing objects location, yields a corresponding Type whose values are pairs, consisting of an instant in time and a value of spatial Type. With this approach, it is possible to represent Temporal development of objects' location within one time interval by using two consecutive values of this Temporal Data Type. Since moving object is basically obtained just by assembling these Temporal developments whose time intervals are disjoint, we also propose an approach for extracting moving objects out of spatio-Temporal Data streams based on user-defined aggregate functions (UDAF) over spatio-Temporal Data Types. With this approach, it is possible to manage moving objects encapsulated within spatio-Temporal Data streams using SQL-like query language.
Ali Frihida - One of the best experts on this subject based on the ideXlab platform.
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modeling trajectories a spatio Temporal Data Type approach
Database and Expert Systems Applications, 2009Co-Authors: Ali Frihida, Donia Zheni, Henda Ben Ghezala, Christophe ClaramuntAbstract:Retrieving and analyzing trajectories favor the study of human behaviors in space and time. Although Time Geography has long proposed a conceptual framework for the interpretation of trajectory Data, there is still a need for Database and semantic models that support representation and manipulation. In fact, the concept of trajectory is rarely addressed as a sui generis Data Type that can be embedded in a Database structure. This paper introduces an algebraic Spatio-Temporal Trajectory Data Type (STT) for the representation of object trajectory. The STT is an abstract Data Type endowed with a set of operations designed as a way to cover the syntax and semantics of a given trajectory. It is considered as a Data structure that can be used for the design and implementation of spatio-Temporal Databases.
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DEXA Workshops - Modeling Trajectories: A Spatio-Temporal Data Type Approach
2009 20th International Workshop on Database and Expert Systems Application, 2009Co-Authors: Ali Frihida, Donia Zheni, Henda Ben Ghezala, Christophe ClaramuntAbstract:Retrieving and analyzing trajectories favor the study of human behaviors in space and time. Although Time Geography has long proposed a conceptual framework for the interpretation of trajectory Data, there is still a need for Database and semantic models that support representation and manipulation. In fact, the concept of trajectory is rarely addressed as a sui generis Data Type that can be embedded in a Database structure. This paper introduces an algebraic Spatio-Temporal Trajectory Data Type (STT) for the representation of object trajectory. The STT is an abstract Data Type endowed with a set of operations designed as a way to cover the syntax and semantics of a given trajectory. It is considered as a Data structure that can be used for the design and implementation of spatio-Temporal Databases.
Emir Meskovic - One of the best experts on this subject based on the ideXlab platform.
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MIPRO - Managing moving objects in the context of spatio-Temporal Data streams
2011Co-Authors: Emir Meskovic, Zdravko Galić, Mirta BaranovićAbstract:Managing moving objects in DSMS has recently been a focus of a relatively intense research. In this paper, we are concerned with Data streams containing a location of a moving object at any time instant. Instead of using spatial and time instant Data Types separately, for representing spatio-Temporal characteristics of Data streams, we propose a unified approach based on specialized Temporal Data Type constructor. This Type constructor, parameterized with a spatial Type representing objects location, yields a corresponding Type whose values are pairs, consisting of an instant of time and a value of spatial Type. With this approach, it is possible to represent Temporal development of an objects' location within one time interval by using two consecutive values of this Temporal Data Type. Since moving object is basically obtained just by assembling these Temporal developments whose time intervals are disjoint, we also propose an approach for extracting moving objects out of spatio-Temporal Data streams based on user-defined aggregate functions (UDAF) over spatio-Temporal Data Types. With this approach, it is possible to manage moving objects encapsulated within spatio-Temporal Data streams using SQL-like query language.
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Mobile Data Management (2) - Managing Moving Objects in Spatio-Temporal Data Streams
2011 IEEE 12th International Conference on Mobile Data Management, 2011Co-Authors: Emir Meskovic, Zdravko Galić, Mirta BaranovićAbstract:Managing moving objects in DSMS has been a focus of a relatively intense research in recent years. In this paper, we are concerned with Data stream tuples containing a location of a moving object at any time instant. Instead of using spatial and time instant Data Types separately, for representing spatio-Temporal component in such Data streams, we propose a use of a specialized Temporal Data Type constructor. This Type constructor parameterized with a spatial Type representing objects location, yields a corresponding Type whose values are pairs, consisting of an instant in time and a value of spatial Type. With this approach, it is possible to represent Temporal development of objects' location within one time interval by using two consecutive values of this Temporal Data Type. Since moving object is basically obtained just by assembling these Temporal developments whose time intervals are disjoint, we also propose an approach for extracting moving objects out of spatio-Temporal Data streams based on user-defined aggregate functions (UDAF) over spatio-Temporal Data Types. With this approach, it is possible to manage moving objects encapsulated within spatio-Temporal Data streams using SQL-like query language.
Mounir Ben Ayed - One of the best experts on this subject based on the ideXlab platform.
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Interactive visual knowledge discovery from Data-based Temporal decision support system:
Information Visualization, 2015Co-Authors: Hela Ltifi, Emna Ben Mohamed, Mounir Ben AyedAbstract:The article aims to present a generic interactive visual analytics solution that provides Temporal decision support using knowledge discovery from Data modules together with interactive visual representations. It bases its design decisions on classification of visual representation techniques according to the criteria of Temporal Data Type, periodicity, and dimensionality. The design proposal is applied to an existing medical knowledge discovery from Data–based decision support system aiming at assisting physicians in the fight against nosocomial infections in the intensive care units. Our solution is fully implemented and evaluated.
