• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.157-162
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• 2002

Recently, location based services, which make use of location information of moving objects, have obtained increasingly high attention. The moving objects are time-evolving spatial objects, that is, their locations are dynamically changed as time varies. Generally, GIS server stores and manages the spatial objects, of which locations are rarely changed. The traditional GIS server, however, has a difficulty to manage the moving objects, due to the fact of locations being frequently changed and the trajectory information (past locations of moving objects) being managed. In this paper, we have designed a moving object server, which stores and manages the locations in order to support various location based services. The moving object server is composed of a location acquisition component, a location storage component, and a location query component. The contribution of this paper is that we integrate the each work for location acquisition, storage, and query into a moving objects server.

• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.9-18
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• 2009

Recently, due to the advanced technologies of mobile devices and wireless communication, there are many studies on telematics and LBS(location-based service) applications. because moving objects usually move on spatial networks, their locations are updated frequently, leading to the degradation of retrieval performance. To manage the frequent updates of moving objects' locations in an efficient way, a new distributed grid scheme, called DS-GRID (distributed S-GRID), and k-NN(k-nearest neighbor) query processing algorithm was proposed[1]. However, the result of k-NN query processing technique may be invalidated as the location of query and moving objects are changed. Therefore, it is necessary to study on continuous k-NN query processing algorithm. In this paper, we propose both MCE-CKNN and MBP(Monitoring in Border Point)-CKNN algorithmss are S-GRID. The MCE-CKNN algorithm splits a query route into sub-routes based on cell and seproves retrieval performance by processing query in parallel way by. In addition, the MBP-CKNN algorithm stores POIs from the border points of each grid cells and seproves retrieval performance by decreasing the number of accesses to the adjacent cells. Finally, it is shown from the performance analysis that our CKNN algorithms achieves 15-53% better retrieval performance than the Kolahdouzan's algorithm.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.59-71
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• 2004

Nearest neighbor query retrieves nearest located target objects, and is very frequently used in mobile environment. In this paper we propose a novel neatest neighbor query processing technique that is able to retrieve nearest located target object from the user who is continuously moving with a direction. The proposed method retrieves objects using the direction property of moving object as well as euclidean distance to target object. The proposed method is applicable to traffic information system, travel information system, and location-based recommendation system which require retrieving nearest located object.

• 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.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.10
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• pp.239-244
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• 2019

In recent mobile environments, query processing costs have been rapidly increasing as users request large amounts of queries. In addition, the server's performance is increasing for many users to handle high-capacity queries, but the workload is increasing continuously. To solve these problems, we use the wireless broadcasting environment. However, in a existing wireless broadcasting environment, servers have a problem sending all the objects they manage to their clients. Therefore, we propose a new R-Bcast combining the advantages of demand-based and wireless broadcasting. R-Bcast is a technique that protects query information and reduces query processing time. Experiments have proved that R-Bcast is superior to conventional techniques.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.67-76
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• 2018

This paper addresses the problem of efficient processing of region monitoring queries. The centralized methods used for existing region monitoring query processing assumes that the mobile object periodically sends location-updates to the server and the server continues to update the query results. However, a large amount of location updates seriously degrade the system performance. Recently, some distributed methods have been proposed for region monitoring query processing. In the distributed methods, the server allocates to all objects i) a resident domain that is a subspace of the workspace, and ii) a number of nearby query regions. All moving objects send location updates to the server only when they leave the resident domain or cross the boundary of the query region. In order to allocate the resident domain to the moving object along with the nearby query region, we use a query index structure that is constructed by splitting the workspace recursively into equal halves. However, However, the above index structure causes unnecessary division, resulting in deterioration of system performance. In this paper, we propose an adaptive split method to reduce unnecessary splitting. The workspace splitting is dynamically allocated i) considering the spatial relationship between the query region and the resultant subspace, and ii) the distribution of the query region. We proposed an enhanced QR-tree with a new splitting method. Through a set of simulations, we verify the efficiency of the proposed split methods.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.429-437
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• 2022

Recently, the demand for a QA (Question Answering) system for human-machine communication has increased. Among the QA systems, a closed domain QA system that can handle spatial-related questions is called GeoQA. In this study, a new type of graph database, LPG (Labeled Property Graph) was used to overcome the limitations of the RDF (Resource Description Framework) based database, which was mainly used in the GeoQA field. In addition, GraphQL (Graph Query Language), an API-type query language, is introduced to address the fact that the LPG query language is not standardized and the GeoQA system may depend on specific products. In this study, database was built so that answers could be retrieved when spatial-related questions were entered. Each data was obtained from the national spatial information portal and local data open service. The spatial relationships between each spatial objects were calculated in advance and stored in edge form. The user's questions were first converted to GraphQL through FOL (First Order Logic) format and delivered to the database through the GraphQL server. The LPG used in the experiment is Neo4j, the graph database that currently has the highest market share, and some of the built-in functions and QGIS were used for spatial calculations. As a result of building the system, it was confirmed that the user's question could be transformed, processed through the Apollo GraphQL server, and an appropriate answer could be obtained from the database.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.6
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• pp.2713-2719
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• 2012

According to increasing of various location-based services, distributed data stream processing techniques have been widely studied to provide high scalability and availability. In previous researches, in order to balance the load of distributed nodes, the geographic characteristics of spatial data stream are not considered. For this reason, distributed operations for adjacent spatial regions increases the overall system load. We propose a operation allocation scheme considering the characteristics of spatial operations to effectively processing spatial data stream in distributed computing environments. The proposed method presents the efficient share maximizing approach that preferentially distributes spatial operations sharing the common query regions to the same node in order to separate the adjacent spatial operations on overlapped regions.

• Spatial Information Research
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• v.6 no.2
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• pp.125-132
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• 1998

The I/O performance for spatial queries is extremely important since the handling of huge amount of multidimensional data is required in spatial databases for geographic information systems. Therefore, we describe representative spatial access methods handling complex spatial objects, z-transform B tree, KDB tree, R tree, MAX tree, to increase I/O performance. In addition, we measure the performance of spatial indexing schemes by testing against various realistic data and query sets. Results from the benchmark test indicates that MAX outperforms other indexing schemes on insertion, range query, spatial join. MAX tree is expected to use as index scheme organizing storage system of GIS in the future.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.459-462
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• 2003

Selectivity estimation of queries not only provides useful information to the query processing optimization but also may give users with a preview of processing results. In this paper, we investigate the problem of selectivity estimation in the context of a spatial dataset. Although several techniques have been proposed in the literature to estimate spatial query result sizes, most of those techniques still have some drawback in the case that a large amount of memory is required to retain accurate selectivity. To eliminate the drawback of estimation techniques in previous works, we propose a new method called MW Histogram. Our method is based on two techniques: (a) MinSkew partitioning algorithm that processes skewed spatial datasets efficiently (b) Wavelet transformation which compression effect is proven. We evaluate our method via real datasets. With the experimental result, we prove that the MW Histogram has the ability of providing estimates with low relative error and retaining the similar estimates even if memory space is small.