• Journal of Information Processing Systems
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• v.2 no.2
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• pp.124-129
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• 2006

With the explosive increase in the generation and utilization of spatiotemporal data sets, many research efforts have been focused on the efficient handling of the large volume of spatiotemporal sets. With the remarkable growth of ubiquitous computing technology, mining from the huge volume of spatiotemporal data sets is regarded as a core technology which can provide real world applications with intelligence. In this paper, we propose a 3-tier knowledge discovery framework for spatiotemporal data mining. This framework provides a foundation model not only to define the problem of spatiotemporal knowledge discovery but also to represent new knowledge and its relationships. Using the proposed knowledge discovery framework, we can easily formalize spatiotemporal data mining problems. The representation model is very useful in modeling the basic elements and the relationships between the objects in spatiotemporal data sets, information and knowledge.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.635-652
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• 2011

In ubiquitous environments, many applications need to process data with time and space dimensions. Because of this, there is growing attention not only on gathering spatiotemporal data in ubiquitous environments, but also on processing such data in databases. In order to obtain the full benefits from spatiotemporal data, we need a data model that naturally expresses the properties of spatiotemporal data. In this paper, we introduce three spatiotemporal data models extended from temporal data models. The main goal of this paper is to determine which data model is less complex in the spatiotemporal context. To this end, we compare their query languages in the complexity aspect because the complexity of a query language is tightly coupled with its underlying data model. Throughout our investigations, we show that it is important to intertwine space and time dimensions and keep one-to-one correspondence between an object in the real world and a tuple in a database in order to naturally express queries in ubiquitous applications.

• The KIPS Transactions:PartD
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• v.12D no.3 s.99
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• pp.375-384
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• 2005

Most of data objects in the real world have spatial and temporal information simultaneously. One of the objectives of spatiotemporal databases is to provide a very expressive framework for spatiotemporal database applications. The object oriented spatiotemporal model can manage spatiotemporal data efficiently because the model is able to store the complete history of any objects. Therefore, in order to handle the spatiotemporal data in object oriented fashion, we proposed a low dimensional spatiotemporal model in the object oriented fashion that extended dimensionally two dimensional spatial model of OpenGIS to fit into the real world information and to include temporal information. In order to proof the proposed model, we design a data provider component which consists of the data source, the session, the command, and the rowset component, and implement it. The proposed four dimensional spatiotemporal data model and provider in the object oriented fashion can be used to store, retrieve and manage the object oriented spatiotemporal data.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.2
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• pp.76-84
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• 2017

This paper presents an efficient method for generating spatiotemporal images in order to detect leukocyte motion in microvessels. Leveraging the constraint that leukocytes move along the contour line of the blood vessel wall, our proposed method efficiently generates spatiotemporal images for leukocyte motion detection. To that end, translational motion caused by in vivo movement is first removed by a template matching method. Second, the blood vessel region is detected by an automatic threshold selection method in order to binarize temporal variance images. Then, the contour of the blood vessel wall is expressed via B-spline function. Finally, using the detected blood vessel wall's contour as an initial curve, the plasma layer for the most accurate position is determined in order to find the spatial axis via snake, and the spatiotemporal images are generated. Experimental results show that the spatiotemporal images are generated effectively through comparison of each step with three images.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.4
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• pp.37-50
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• 2003

In the paper, we describe the query extension techniques for spatiotemporal query functionalities on object-relational DBMS. The spatial objects in real world change the shapes over time. Spatiotemporal databases support to manage a temporal dimension as well as a spatial dimension for history of the objects. The proposed techniques can make conventional object-relational databases to support spatiotemporal databases system by the implementation and inheritance of abstract data types. We define and implement spatial and temporal classes as superclass. And, spatiotemporal classes inherits and extends the classes. The proposed extensions make it easy that conventional database systems not only are transformed into the spatiotemporal database systems, but also do not need to be changed to support spatiotemporal applications.

• Journal of KIISE:Databases
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• v.31 no.3
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• pp.205-218
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• 2004

As the development of database technology for managing spatiotemporal data, new types of spatiotemporal application services that need the spatiotemporal knowledge discovery from the large volume of spatiotemporal data are emerging. In this paper, a new 3-layered discovery framework for the development of spatiotemporal knowledge discovery techniques is proposed. The framework supports the foundation model in order not only to define spatiotemporal knowledge discovery problem but also to represent the definition of spatiotemporal knowledge and their relationships. Also the components of spatiotemporal knowledge discovery system and its implementation model are proposed. The discovery framework proposed in this paper satisfies the requirement of the development of new types of spatiotemporal knowledge discovery techniques. The proposed framework can support the representation model of each element and relationships between objects of the spatiotemporal data set, information and knowledge. Hence in designing of the new types of knowledge discovery such as spatiotemporal moving pattern, the proposed framework can not only formalize but also simplify the discovery problems.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.2
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• pp.162-169
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• 2011

Land information is the real-time spatial thing which must be considered with spatial and time factors. This study aims to apply and implement an appropriate spatiotemporal model for land information by exploring spatiotemporal data models which have been suggested in the previous studies. The implemented spatiotemporal model in this study is characterized by time and attribute. In the time aspect, it is divided by valid time and transaction time, and in the attribute aspect, includes the related information such as area and ownership. At the spatial point of view, the model has a spaghetti information structure as reducing information overlapped by managing the spatial information coordinates. The spatiotemporal land information model in this study facilitates representing the quality of attribute, spatial and time information.

• 한국공간정보시스템학회:학술대회논문집
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• 2005.11a
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• pp.61-66
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• 2005

Spatiotemporal data mining represents the confluence of several fields including spatiotemporal databases, machine loaming, statistics, geographic visualization, and information theory. Exploration of spatial data mining and temporal data mining has received much attention independently in knowledge discovery in databases and data mining research community. In this paper, we introduce an algorithm Max_MOP for discovering moving sequences in mobile environment. Max_MOP mines only maximal frequent moving patterns. We exploit the characteristic of the problem domain, which is the spatiotemporal proximity between activities, to partition the spatiotemporal space. The task of finding moving sequences is to consider all temporally ordered combination of associations, which requires an intensive computation. However, exploiting the spatiotemporal proximity characteristic makes this task more cornputationally feasible. Our proposed technique is applicable to location-based services such as traffic service, tourist service, and location-aware advertising service.

• The Transactions of the Korea Information Processing Society
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• v.5 no.10
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• pp.2467-2478
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• 1998

The spatiotemporal databases support historical informations as well as spatial managements for the objects in the real world, and can be efficiently used to various applications such as geographic information system, urban plan system, car navigation system. Although there are so far several pioneering works in spatioemporal data modeling, it is little to study on spatiotemporal query language. So in this paper, we at first survey a modeling technique that makes spatiotemporal objects into databases, and then show some sighificant functions supported by query language. Also we suggest a new spatiotemporal database query language, entitled as STQL, which make users to enable to manage efficient historical information as well as spatial management function on the basis of relational query language, SQL. Also the proposed STQL, shows their operationsl in spatiotemporal daabases.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.551-554
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• 2003

Aggregate operator which belongs to query operations are important in specialized systems such as geographic information system(GIS) and spatial database system. Most of data describing objects in the real world are characterized by space and time attributes. Till now, however, works on aggregate operations have only dealt with spatial or temporal aspect of object. The current demand of aggregate operations relates to spatiotemporal data which are contained both spatial and temporal data concurrently. Therefore, work on spatiotemporal operations is focused on database area. In this paper, we propose spatiotemporal aggregate functions that operate on spatiotemporal data. Above all, we support spatiotemporal aggregate functions on the basis of three dimensional spatiotemporal models that are defined with the linear one dimensional temporal domain. The proposed algorithms are evaluated through some implementation results. We are sure that the achievement of our work is useful and efficient.