• Spatial Information Research
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• v.8 no.1
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• pp.155-170
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• 2000

When we use R-Tree,a spatial index, to find objects matches some predicate, it often leads to an incorrect result of perform filtering step only with MBR. And , each candidates need to be inspected to conform if it really satisfies with given query, so called, 'refinement step'. In refinement step. we should perform disk I/O and expansive spatial operations which is the cause of increasing retrieval costs. Therefore, to minimize the number of candidate after filtering step, two-phase filtering methods were studied, but there was many problems such as inefficiency of filtering,maintenance of additional informations and reconstruction of data resulted from the loss of original information. So , in this paper, I propose an Extended R-Tree which provides ability to retrieve spatial objects only with some simple logical operations using Grid Table, truth table strong the information about the existence of spatial objects, in second filtering step. Consequently , this Extended R-Tree using Grid Filter has low cost of operation for filtering because of efficient second filtering step, and better filtering efficiency caused by high quality of approximation.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.453-463
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• 2002

With the prevalence of multi-dimensional data such as images, content-based retrieval of data is becoming increasingly important. To handle multi-dimensional data, multi-dimensional index structures such as the R-tree, Rr-tree, TV-tree, and MVP-tree have been proposed. Numerous research results on how to effectively manipulate these structures have been presented during the last decade. Query processing strategies, which is important for reducing the processing time, is one such area of research. In this paper, we propose query processing algorithms for R-tree based structures. The novel aspect of these algorithms is that they make use of the notion of VP filtering, a concept borrowed from the MVP-tree. The filtering notion allows for delaying of computational overhead until absolutely necessary. By so doing, we attain considerable performance benefits while paying insignificant overhead during the construction of the index structure. We implemented our algorithms and carried out experiments to demonstrate the capability and usefulness of our method. Both for range query and incremental query, for all dimensional index trees, the response time using VP filtering was always shorter than without VP filtering. We quantitatively showed that VP filtering is closely related with the response time of the query.

• Spatial Information Research
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• v.19 no.1
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• pp.117-126
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• 2011

Recently, AR applications provide location-based spatial information by GPS. Also, the spatial information is displayed by the angle of the camera. So far, traditional spatial indexes in spatial database field retrieve and filter spatial information by the minimum bounding rectangle (MBR) algorithm.(ex. R-tree) MBR strategy is a useful technique in the geographic information systems and location based services. But MBR technique doesn't reflect the characteristics of spatial queries in AR. Spatial queries of AR applications have high possibility of the dead space area between MBRs of non-leaf node and query area. We propose triangle node filtering algorithm that improved efficiency of spatial retrieval used the triangle node filtering techniques by exclusion the dead space. In this paper, the proposed algorithm has been implemented on PostgreSQL/PostGIS. Experimental results show the spatial retrieval that using the proposed algorithm better performance than the spatial retrieval that of the minimum bounding rectangle algorithm.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.45-48
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• 2011

본 논문에서는 다양한 타입의 위치기반 데이터들을 하나의 R-tree로 통합합 $R^m$-tree의 구조와 이 $R^m$-tree를 이용하여 질의 포인트로부터 각 타입에서 k개의 가까운 위치기반 데이터를 찾는 mkNN(multi-type k nearest neighbor) 질의 처리기법을 제안하였다. 특히, 다양한 타입의 위치기반 데이터들을 각 타입별로 독립된 R-tree로 유지하지 않고, 하나의 $R^m$-tree로 통합하여 관리함으로써 mkNN 질의 처리시 같은 레벨의 공간의 반복탐색을 줄일 수 있도록 고안하였다. 그리고 각 타입 t에 대한 위치데이터를 관리하는 부가적인 타입정보 자료구조로서 위치정보를 담은 TMBR, 데이터 개수정보를 담은 $I_t$-entry를 새로이 고안하여 mkNN질의 처리시 효율적인 휠터링(filtering)과 검색과정이 이루어지도록 하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1584-1590
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• 2008

The combined query which consists of the region and trajectory query finds trajectories of moving objects which locate in a certain region. The trajectory query is very informant factor to determine query performance because it processes a point query continuously to find predecessors. This results in bad performance due to revisiting nodes in an index. This paper suggests an efficient method for the combined query based on the 3-dimensional R-tree which has good performance of the region query. The basic idea is that we define the least common search line which enables to search single path and a filtering method based on prediction without revisiting nodes.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.294-297
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• 2000

Among the multi-dimensional query types, ranking query is needed if we want the object one by one until we satisfy for the result. In multi-dimensional indexing structures like R-tree or its variants, not many methods are introduced in this area. In this paper, we introduce new ranking query processing algorithm which use the filtering mechanism in the R-tree variants.

• Spatial Information Research
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• v.19 no.5
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• pp.63-74
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• 2011

Recently, there has been much interest in the spatial query which energy-efficiently acquires sensor readings from sensor nodes inside specified geographical area of interests. The centralized approach which performs the spatial query at a server after acquiring all sensor readings, though simple, it incurs high wireless transmission cost in accessing all sensor nodes. In order to remove the high wireless transmission cost, various in-network spatial indexing schemes have been proposed. They have focused on reducing the transmission cost by performing distributed spatial filtering on sensor nodes. However, these in-network spatial indexing schemes have a problem which cannot optimize both the spatial filtering and the wireless routing among sensor nodes, because these schemes have been developed by simply applying the existing spatial indexing schemes into the in-network environment. Therefore, we propose a new distributed spatial indexing scheme of the GR-tree. The GR-tree which form s a MBR-based tree structure, can reduce the wireless transmission cost by optimizing both the efficient spatial filtering and the wireless routing. Finally, we compare the existing spatial indexing scheme through extensive experiments and clarify our approach's distinguished features.

• Journal of KIISE:Databases
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• v.30 no.6
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• pp.593-605
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• 2003

Since spatial join processing consumes much time, several algorithms have been proposed to improve spatial join performance. The M-way R-tree join (MRJ) is a join algorithm which synchronously traverses M R-trees in the M-way spatial join. In this paper, we introduce indirect predicates which do not directly come from the multi-way join conditions but are indirectly derived from them. By applying the concept of indirect predicates to MRJ, we improve the performance of MRJ. We call such a multi-way R-tree join algorithm using indirect predicates indirect predicate filtering (IPF). Through experiments using synthetic data and real data, we show that IPF significantly

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.344-356
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• 2001

This paper deals with the subsequence searching problem under time-warping in sequence databases. Our work is motivated by the observation that subsequence searches slow down quadratically as the average length of data sequences increases. To resolve this problem, the Segment-Based Approach for Subsequence Searches (SBSS) is proposed. The SBASS divides data and query sequences into a series of segments, and retrieves all data subsequences that satisfy the two conditions: (1) the number of segments is the same as the number of segments in a query sequence, and (2) the distance of every segment pair is less than or equal to a tolerance. Our segmentation scheme allows segments to have different lengths; thus we employ the time warping distance as a similarity measure for each segment pair. For efficient retrieval of similar subsequences, we extract feature vectors from all data segments exploiting their monotonically changing properties, and build a spatial index using feature vectors. Using this index, queries are processed with the four steps: (1) R-tree filtering, (2) feature filtering, (3) successor filtering, and (4) post-processing. The effectiveness of our approach is verified through extensive experiments.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.1-10
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• 2008

In wireless internet, the location information of the user is one of the important resources for many applications. One of these applications is Location-Based Services (LBSs) which are being popular. Because, in the LBS system, users request a location-based query to LBS servers by sending their exact location, the location information of the users can be misused by adversaries. In this regard, there must be a mechanism which can deal with privacy protection of the users. In this paper, we propose a cloaking method considering both features of K-anonymity and L-diversity. Our cloaking method creates a minimum cloaking region by finding L number of buildings (L-diversity) and then finding number of users (K-anonymity). To support this, we use a R*-tree based index structure and use filtering methods especially for the m inimum cloaking region. Finally, we show from a performance analysis that our method outperforms the existing grid based cloaking method.