• Journal of KIISE:Databases
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• v.30 no.5
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• pp.521-531
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• 2003

Multi-level geographic data can be mainpulated by a window query such as a zoom operation. In order to handle multi-level geographic data efficiently, a spatial indexing method supporting a window query is needed. However, the conventional spatial indexing methods are not efficient to access multi-level geographic data quickly. To solve it, other a few spatial indexing methods for multi-level geographic data are known. However these methods do not support all types of multi-level geographic data. This paper presents a new efficient spatial indexing method, the MLR-tree for window query of multi-level geographic data. The MLR-tree offers both high search performance and no data redundancy. Experiments show them. Moreover, the MLR-tree supports all types of multi-level geographic data.

• Journal of Internet Computing and Services
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• v.3 no.2
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• pp.1-13
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• 2002

Recently, Internet GIS(Geographic Information System) is increasing. From the results, more efficient spatial data retrieval is needed. For more efficient retrieval, a spatial indexing method is needed. This paper proposes an efficient spatial indexing method for levelized geometric data retrieval. Previous indexing methods are not adequate to retrieve levelized geometric data. For the effects, a few indexing methods for levelized geometric data, are known. But these methods support only a tew kinds of levelized geometric data. The proposed method supports all kind of levelized geometric data and outperforms to the previous method both in retrieval time and memory capacity.

• The Transactions of the Korea Information Processing Society
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• v.6 no.12
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• pp.3469-3476
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• 1999

In spatial database based on spatial data structures, instead of one-dimensional indexing structure, new indexing structure which corresponds to multi-dimensional features of spatial objects is required. In order to meet those requirements, in this paper we proposed new indexing structure for efficient retrieval of spatial database by carrying through the feature analysis of conventional multi-dimensional indexing structures. To improve the sequential search method of supernodes in the conventional X-tree and to reduce the retrieval time in case of generating the huge supernode, we proposed a indexing structure integrating the kd-tree based on point index structure into the X-tree. We implemented the proposed indexing structure and analyzed its retrieval time according to the dimension and distribution of experimental data.

• Journal of Korea Multimedia Society
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• v.4 no.3
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• pp.197-204
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• 2001

In order to increase the performance of spatial database systems, a spatial indexing method is necessary to manage spatial objects efficiently in both dynamic and static environments. A spatial indexing method considering a spatial locality is required to increase the retrieval performance. And the spatial locality is related to the location property of objects. The previous spatial indexing methods did not consider the circular location property of objects. In this paper, we introduce the CR-Tree that is a spatial index structure for clustering spatially adjacent objects in which a search space is constructed with the circular and linear domains. Using a spatial index structure considered a circular location property of objects, we show that high hit ratio and bucket utilization are increased through the simulation.

• 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.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.10-12
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• 2004

Nowadays, with the rapid emergence of XML as a standard for data exchange over the Internet had led to considerable interest In the problem of data management requirements such as the need to store and query XML documents in which the location path languages Xpath is of particular important for XML application since it is a core component of many XML processing standards such as XSLT or XQuery, This parer gives a brief overview about method and design by applying a new spatial-based indexing method namely Xp-free that used for supporting Xpath. Spatial indexing technique has been proved its capacity on searching in large databases. Based on accelerating a node using planar as combined with the numbering schema, we devise efficiently derivative algorithms, which are simple, but useful. Besides that, it also allows to trace all Its relative nodes of context node In a manner supporting queries natural to the types especially Xpath queries with predicates.

• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.15-22
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• 2004

Map services for cellular phone have problem for implementation, which are the limitation of a screen size. To effectively represent map data on screen of celluar phone, it need a process which translate a detailed map data into less detailed data using map generalization, and it should manipulate zoom in out quickly by leveling the generalized data. However, current spatial indexing methods supporting map generalization do not support all map generalization operations. In this paper, We propose a leveled spatial indexing method, LMG-tree, supporting map generalization and presents the results of performance evaluation.

• Journal of the Korean Association of Geographic Information Studies
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• v.8 no.1
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• pp.63-74
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• 2005

The telematics device, which is a typical embedded system on the transportation or vehicle, requires the embedded spatial DBMS based on RTOS (Real Time Operating System) for processing the huge spatial data in real time. This spatial DBMS can be developed very easily by SQL3 functions of the ORDBMS such as UDT (user-defined type) and UDF (user-defined function). However, developing index suitable for the embedded spatial DBMS is very difficult. This is due to the fact that there is no built-in SQL3 functions to construct spatial indexes. In this study, we compare and analyze both Generalized Search Tree and Relational Indexing methods which are suggested as common ways of developing User-Defined Indexes nowadays. Two implementations of R-Tree based on each method were done and region query performance test results were evaluated for suggesting a suitable indexing method of an embedded spatial DBMS, especially for telematics devices.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.10
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• pp.1862-1878
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• 2011

With the advances in wireless communication technology and the advent of smartphones, research on location-based services (LBSs) is being actively carried out. In particular, several spatial index methods have been proposed to provide efficient LBSs. However, finding an optimal indexing method that balances query performance and index size remains a challenge in the case of wireless environments that have limited channel bandwidths and device resources (computational power, memory, and battery power). Thus, mechanisms that make existing spatial indexing techniques more efficient and highly applicable in resource-limited environments should be studied. Bitmap-based Spatial Indexing (BSI) has been designed to support LBSs, especially in wireless broadcast environments. However, the access latency in BSI is extremely large because of the large size of the bitmap, and this may lead to increases in the search time. In this paper, we introduce a Selective Bitmap-based Spatial Indexing (SBSI) technique. Then, we propose an Adaptive Bitmap-based Spatial Indexing (ABSI) to improve the tuning time in the proposed SBSI scheme. The ABSI is applied to the distribution of geographical objects in a grid by using the Hilbert curve (HC). With the information in the ABSI, grid cells that have no objects placed, (i.e., 0-bit information in the spatial bitmap index) are not tuned during a search. This leads to an improvement in the tuning time on the client side. We have carried out a performance evaluation and demonstrated that our SBSI and ABSI techniques outperform the existing bitmap-based DSI (B DSI) technique.

• The Journal of Korean Association of Computer Education
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• v.6 no.4
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• pp.49-59
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• 2003

In order to index exactly moving objects(vehicle, mobile phone, PDA, etc.) in a mobile database, continuous updates of their locations arc inevitable as well as time-consuming. In this paper, we propose a spatial indexing method of moving objects for the efficient mobile map services. In detail, we analyze the characteristics of both the method to re-index all the objects after each time period and the method to update immediately the locations on reporting their locations. We also newly propose a bucket split method using the properties of moving objects in order to minimize the number of database updates. The experiments conducted on the environments of moving object show that the proposed indexing method is appropriate to map services for mobile devices.