• Journal of Platform Technology
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• v.11 no.1
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• pp.52-59
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• 2023

The importance of spatio-temporal trajectories for contact tracing has increased due to the recent COVID-19 pandemic. Spatio-temporal trajectories store time and spatial data of moving objects. In this paper, I propose query processing for spatio-temporal trajectories of moving objects. The spatio-temporal trajectory model of moving objects has point type spatial data for storing locations and timestamp type temporal data for time. A trajectory query is a query to search for pairs of users who have been in close contact by boarding the same bus. To process the trajectory query, I use the Geolife dataset provided by Microsoft. The proposed trajectory query processing method divides trajectory data by date and checks whether users' trajectories were nearby for each date to generate information about contacts as the result.

• The Transactions of the Korea Information Processing Society
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• v.6 no.4
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• pp.841-850
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• 1999

Many commercial database systems maintain histograms to summarize the contents of relations, permit efficient estimation of query result sizes, and access plan costs. In spatial database systems, most query predicates consist of topological relationship between spatial objects, and ti is ver important to estimate the selectivity of those predicates for spatial query optimizer. In this paper, we propose a selectivity estimation scheme for spatial topological predicates based on the multi-dimensional histogram and the transformation scheme. Proposed scheme applies two partition strategies on transformed object space to generate spatial histogram, and estimates the selectivity of topological predicates based on the topological characteristic of transformed space. Proposed scheme provides a way for estimating the selectivity without too much memory space usage and additional I/Os in spatial query optimizer.

• Proceedings of the Korea Database Society Conference
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• 1997.10a
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• pp.472-482
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• 1997

Multi-dimensional data play a crucial role in various fields, as like computer graphics, geographical information system, and multimedia applications. Indexing method fur multi-dimensional data Is a very Important factor in overall system performance. What is proposed in this paper is a new dynamic access method for spatial objects called HL-CIF(Hierarchically Layered Caltech Intermediate Form) tree which requires small amount of storage space and facilitates efficient query processing. HL-CIF tree is a combination of hierarchical management of spatial objects and CIF tree in which spatial objects and sub-regions are associated with representative points. HL-CIF tree adopts "centroid" of spatial objects as the representative point. By reflecting objects′sizes and positions in its structure, HL-CIF tree guarantees the high spatial locality of objects grouped in a sub-region rendering query processing more efficient.

• Journal of Korea Spatial Information System Society
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• v.1 no.2 s.2
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• pp.137-149
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• 1999

Spatial database systems in client-server environment have network overload due to the large amount of spatial data transmission. Users use the window query that loads partial region of a whole map for quick response time in the environment. A series of window query such as screen movement, enlargement or shrinkage requires data in similar region and this increases network overload by re-transmitting the same data in intersected region with the earlier transmitted region. Removing the transmitted data from query results can solve this problem. In this paper, we design and implement a spatial object manager in order to remove the intersected region occurred by a series of window query. The spatial object manager manages the object identifiers of transmitted objects and removes transmitted objects from spatial objects of the query result by using the removal technique of the intersected region for the transmission and comparison. We utilize GEOMania Millennium server, an open client-server spatial database system, as spatial object manager in this paper. The result of the performance evaluation shows that the spatial object manager removes the transmission of the data redundancy, reduces network overload and improves the overall system performance.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.101-104
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• 2007

Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.

• Journal of KIISE:Computing Practices and Letters
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• v.5 no.5
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• pp.543-552
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• 1999

The iterator technique which is used for implementing physical operators of the query executor is known for its efficiency and extensibility. The most widely used technique for processing an operator on spatial objects is to process by dividing it into the filter step and the refinement step. Recently, there was a research for an optimizer which can generate more efficient query execution plans than those of traditional methods by separating a spatial operator into filter and refinement steps in the level of the object algebra. But, traditional query executors were not designed considering such query execution plans. So they have no function of transmitting the result of the filter operation between operators. We propose two methods, the probe technique and the tag technique, which transmit the result of the filter operator when using the iterator in the query execution plan in which operators are separated by filter/refinement steps and other operators can be allowed between the steps. Whereas the probe technique extends the state record within an operator, the tag technique stores the result of a filter step in an intermediate result in the form of the tag. Based on the comparison of these methods, we design and implement a query executor using the tag technique that is superior in extensibility. The implemented query executor can execute operations defined in the Spatial Object Algebra(SOA) to process an extended OQL for spatial queries.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.455-457
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• 2003

Diverse researches are working moving objects. The most important activities in a moving object database system are query and analysis of spatio -temporal data providing decision-making and problem solving support. Traditional spatial database query language and tools are inappropriate of the real world entities. This paper presents a spatio-temporal query and analysis tool with visual environment. It provides effective, interactive and user-friendly as well as statistic analysis. The moving objects database system stores plentiful moving objects data and performs spatio-temporal and nonspatio-temporal queries.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.377-386
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• 2001

In spatial database system, spatial view is supported for efficient access method to spatial database and is managed by materialization and non-materialization technique. In non-materialization technique, repeated execution on the same query makes problems such as the bottle-neck effect of server-side and overloads on a network. In materialization technique, view maintenance technique is very difficult and maintenance cost is too high when the base table has been changed. In this paper, the SVMT (Spatial View Materialization Technique) is proposed by using R-tree re-construction. The SVMT is a technique which constructs a spatial index according to the distribution ratio of objects in spatial view. This ratio is computed by using a SVHR (Spatial View Height in R-tree) and SVOC (Spatial View Object Count). If the ratio is higher than the average, a spatial view is materialized and the R-tree index is re-used. In this case, the root node of this index is exchanged a node which has a MBR (Minimum Boundary Rectangle) value that can contains the whole region of spatial view at a minimum size. Otherwise, a spatial view is materialized and the R-tree is re-constructed. In this technique, the information of spatial view is managed by using a SVIT (Spatial View Information Table) and is stored on the record of this table. The proposed technique increases the speed of response time through fast query processing on a materialized view and eliminates additional costs occurred from repeatable query modification on the same query. With these advantages, it can greatly minimize the network overloads and the bottle-neck effect on the server.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.203-214
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• 2002

This paper presents a physical database design methodology for spatial access structures using transformation techniques in spatial database systems. Recently, many spatial access structures have been proposed in the literature. However, there has been no effort for their physical database design. We first show that most spatial queries in the original space are transformed into one type of range queries in the transform space, and then propose a method for finding the optimal configuration of spatial access structures by using the relationship between the shapes of query regions, that are correspond to the range queries, and page regions, that are correspond to data pages, in the transform space. For performance evaluation, we perform extensive experiments with the MBR-MLGF, a spatial access structure using transformation techniques, using various types of queries and data distributions. The results indicate that our proposed method builds optimal MBR-MLGF according to the query types. When the interval ratio of a transformed four-dimensional query region is 1 : 16 : 256 : 4096, the performance of the proposed method is enhanced by as much as five times over that of the conventional cyclic splitting method. The result confirms that the proposed physical database design methodology is useful in a practical way.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.721-725
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• 2004

Multiple-count problem is occurred when rectangle objects span across several buckets. The Cumulative Density (CD) histogram is a technique which solves multiple-count problem by keeping four sub-histograms corresponding to the four points of rectangle. Although it provides exact results with constant response time, there is still a considerable issue. Since it is based on a query window which aligns with a given grid, a number of errors may be occurred when it is applied to real applications. In this paper, we proposed selectivity estimation techniques using the generalized cumulative density histogram based on two probabilistic models: (1) probabilistic model which considers the query window area ratio, (2) probabilistic model which considers intersection area between a given grid and objects. In order to evaluate the proposed methods, we experimented with real dataset and experimental results showed that the proposed technique was superior to the existing selectivity estimation techniques. The proposed techniques can be used to accurately quantify the selectivity of the spatial range query on rectangle objects.