• Journal of Internet Computing and Services
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• v.12 no.6
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• pp.43-51
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• 2011

The recent development of the technology for wireless mobile computing and applied technology for location-based services has made it possible to support query processing faster than that in the past. However, some technological limitations on hardware and software still exist. The most critical aspects of query processing are accuracy and speed. For improving the accuracy, it is required that detailed information on the data involved in query processing be saved. In this case, the amount of information on the data increases, which decreases the speed. On the other hand, for increasing the speed, it is necessary to reduce the broadcast cycle, which enables rapid data acquisition as desired. In this case, because of insufficient index information, the listen time for the client increases, which may cause unnecessary energy consumption. Therefore, a trade-off occurs between the accuracy and speed. This paper proposes a hierarchical bitmap-based spatial index (HBI) as a solution for the aforementioned problems. HBI describes an object with 0 and 1 on the Hilbert curve map. It reduces the broadcast cycle by decreasing the index size on the basis of bit information and tree structure. Therefore, it is able to shorten the listen time and query processing time. In addition, HBI enables the detection of the locations of all the objects so that it is possible selectively listen to a broadcast. A performance evaluation of the proposed technique demonstrates that it is excellent.

• Journal of Korea Spatial Information System Society
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• v.10 no.3
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• pp.1-18
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• 2008

Because we can usually get many information through analyzing trajectories of moving objects on spatial networks, efficient trajectory index structures are required to achieve good retrieval performance on their trajectories. However, there has been little research on trajectory index structures for spatial networks such as FNR-tree and MON-tree. Also, because FNR-tree and MON-tree store the segment unit of moving objects, they can't support the trajectory of whole moving objects. In this paper, we propose an efficient trajectory index structures based on signatures on a spatial network, named SigMO-Tree. For this, we divide moving object data into spatial and temporal attributes, and design an index structure which supports not only range query but trajectory query by preserving the whole trajectory of moving objects. In addition, we divide user queries into trajectory query based on spatio-temporal area and similar-tralectory query, and propose query processing algorithms to support them. The algorithm uses a signature file in order to retrieve candidate trajectories efficiently Finally, we show from our performance analysis that our trajectory index structure outperforms the existing index structures like FNR-Tree and MON-Tree.

• Journal of the Korean Society for information Management
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• v.21 no.3
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• pp.251-267
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• 2004

The purpose of this study is to generate the local level knowledge structure of a single document, similar to end-of-the-book indexes and table of contents of printed material through the use of term clustering and cluster representative term selection. Furthermore, it aims to analyze the functionalities of the knowledge structure. and to confirm the applicability of these methods in user-friend1y information services. The results of the term clustering experiment showed that the performance of the Ward's method was superior to that of the fuzzy K -means clustering method. In the cluster representative term selection experiment, using the highest passage frequency term as the representative yielded the best performance. Finally, the result of user task-based functionality tests illustrate that the automatically generated knowledge structure in this study functions similarly to the local level knowledge structure presented In printed material.

• The KIPS Transactions:PartD
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• v.11D no.4
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• pp.809-822
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• 2004

In this paper, we propose a concurrency control algorithm based on R-tree for spatial database management system. The previous proposed algorithms can't prevent problem that search operation is to be blocking during update operations. In case of multidimensional indexes like R-tree, locking of update operations may be locked to several nodes, and splitting of nodes have to lock a splitting node for a long time. Therefore search operations have to waiting a long time until update operations unlock. In this paper we propose new algorithms for lock-free search operation. First, we develop a new technique using a linked-list technique on the node. The linked-list enable lock-free search when search operations search a node. Next, we propose a new technique using a version technique. The version technique enable lock-free search on the node that update operations is to be splitting.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.4
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• pp.313-332
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• 2014

With the increased creation, distribution, and use of image in context of the development of digital technologies and internet, research endeavors have accumulated drastically. As two dominant aspects of image retrieval have been considered content-based and concept-based image retrieval, concept-based image retrieval has been focused in the field of Library and Information Science. This study aims to systematically review the accumulated research of image retrieval from the perspective of LIS field. In order to achieve the purpose of this study, two data sets were prepared: a total of 282 image retrieval research papers from Web of Science, and a total of 35 image retrieval research from DBpia in Kore for comparison. For data analysis, systematic review methodology was utilized with bibliographic analysis of individual research papers in the data sets. The findings of this study demonstrated that two sub-areas, image indexing and description and image needs and image behavior, were dominant. Among these sub-areas, the results indicated that there were emerging areas such as collective indexing, image retrieval in terms of multi-language and multi-culture environments, and affective indexing and use. For the user-centered image retrieval research, college and graduate students were found prominent user groups for research while specific user groups such as medical/health related users, artists, and museum users were found considerably. With the comparison with the distribution of sub-areas of image retrieval research in Korea, considerable similarities were found. The findings of this study expect to guide research directions and agenda for future.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.225-236
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• 2011

Various applications of LBS (Location Based Services) are being developed to provide the customized service depending on user's location with progress of wireless communication technology and miniaturization of personalized device. To effectively process an amount of vehicles' location data, LBS requires the techniques such as vehicle observation, data communication, data insertion and search, and user query processing. In this paper, we propose the historical location index, GIP-FB (Group Insertion tree with Flexible Buffer Node) and the flexible buffer node technique to adjust the cost of data insertion and search. the designed GIP+ based index employs the buffer node and the projection storage to cut the cost of insertion and search. Besides, it adjusts the cost of insertion and search by changing the number of line segments of the buffer node with user defined time interval. In the experiment, the buffer node size influences the performance of GIP-FB by changing the number of non-leaf node of the index. the proposed flexible buffer node is used to adjust the performance of the historical location index depending on the applications of LBS.

• Journal of KIISE:Databases
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• v.35 no.5
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• pp.447-458
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• 2008

In this paper, we address an efficient processing scheme for k-nearest neighbor queries to retrieve k static objects in road network databases. Existing methods cannot expect a query processing speed-up by index structures in road network databases, since it is impossible to build an index by the network distance, which cannot meet the triangular inequality requirement, essential for index creation, but only possible in a totally ordered set. Thus, these previous methods suffer from a serious performance degradation in query processing. Another method using pre-computed network distances also suffers from a serious storage overhead to maintain a huge amount of pre-computed network distances. To solve these performance and storage problems at the same time, this paper proposes a novel approach that creates an index for moving objects by approximating their network distances and efficiently processes k-nearest neighbor queries by means of the approximate index. For this approach, we proposed a systematic way of mapping each moving object on a road network into the corresponding absolute position in the m-dimensional space. To meet the triangular inequality this paper proposes a new notion of average network distance, and uses FastMap to map moving objects to their corresponding points in the m-dimensional space. After then, we present an approximate indexing algorithm to build an R*-tree, a multidimensional index, on the m-dimensional points of moving objects. The proposed scheme presents a query processing algorithm capable of efficiently evaluating k-nearest neighbor queries by finding k-nearest points (i.e., k-nearest moving objects) from the m-dimensional index. Finally, a variety of extensive experiments verifies the performance enhancement of the proposed approach by performing especially for the real-life road network databases.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12B
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• pp.1022-1036
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• 2004

In mobile cellular network the ever-changing location of a mobile host necessitates the continuous tracking of its current position and efficient management of location information. A database called Home Location Register(HLR) plays a major role in location management in this distributed environment, providing table management, index management, and backup management facilities. The objectives of this paper are to identify the p개blems of the current HLR system through rigorous analysis, to suggest solutions to them, and to propose a new architecture for the HLR system. In the HLR system, a main memory database system is used to provide real-time accesses and updates of subscriber's information. Thus it is suggested that the improvement bemade to support better real-time facilities, to manage subscriber's information more reliably, and to accommodate more subscribers. In this paper, I propose an efficient backup method that takes into account the characteristics of HLR database transactions. The retrieval speed and the memory usage of the two-level index method are better than those of the T-tree index method. Insertion md deletion overhead of the chained bucket hashing method is less than that of modified linear hashing method. In the proposed backup method, I use two kinds of dirty flags in order to solve the performance degradation problem caused by frequent registration-location operations. Performance analysis has been performed to evaluate the proposed techniques based on a system with subscribers. The results show that, in comparison with the current techniques, the memory requirement is reduced by more than 62%,directory operations, and backup operation by more than 80%.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.184-186
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• 2002

기존의 색인 기법들은 차원의 수가 증가할수록 검색 성능이 급격히 저하되는 문제를 지니고 있다. 이문제를 극복하기 위하여 CBF 기법이 제안되었다. 그러나 CBF 기법은 데이터 양이 증가함에 따라 검색 성능이 선형적으로 감소하는 문제가 존재한다. 이를 해결하기 위해 다수의 디스크를 수평 분할 방법을 이용하여 디클러스터링(declustering)을 하는 병렬 CBF 기법이 제안되었다. 본 논문에서는 수평 분할 방법을 이용한 병렬 CBF (Parallel CBF) 기법을 삽입시간, 범위 질의 검색시간, k-최근접 질의 검색시간, 데이터의 편중도 측면에서 성능 평가를 수행한다. 아울러, 병렬 CBF 기법을 기존 CBF 기법과 성능 비교를 수행하며, 이를 통해 병렬 CBF 기법이 기존 CBF 기법보다 우수한 검색 성능을 나타냄을 보인다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.250-252
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• 2002

기존의 색인 기법들은 차원의 수가 증가할수록 검색 성능이 급격히 저하되는 문제를 지니고 있으며. 이를 극복하기 위하여 CBF 기법이 제안되었다. 그러나 CBF 기법은 데이터 양이 증가함에 따라 검색성능이 선형적으로 감소하는 문제가 존재한다. 이를 해결하기 위해 다수의 디스크를 수령 분할 방법을 이용하여 디클러스터링(declustering)을 하는 병렬 CBF 기법이 제안되었다. 본 논문에서는 병렬 CBF기법을 여러 대의 리눅스 컴퓨터를 이용한 클러스터 시스템 환경 하에서 구현하고, 삽입시간, 범위 질의 검색시간, k-최근접 질의 검색시간 측면에서 성능 평가를 수행한다. 아울러, 클러스터 시스템 환경 하에서의 병렬 CBF 기법을 기존 CBF 기법과 성능 비교를 수행하며, 이를 통해 병렬 CBF 기법이 기존 CBF 기법보다 우수한 검색 성능을 나타냄을 보인다.