• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.597-618
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• 2019

Categorical range aggregation, which is conceptually equivalent to running a range aggregation query separately on multiple datasets, returns the query result on each dataset. The challenge is when the number of dataset is as large as hundreds or thousands, it takes a lot of computation time and I/O. In previous work, only a single dimension of the range restriction has been solved, and in practice, more applications are being used to calculate multiple range restriction statistics. We proposed MCRI-Tree, an index structure designed to solve multi-dimensional categorical range aggregation queries, which can utilize main memory to maximize the efficiency of CRA queries. Specifically, the MCRI-Tree answers any query in $O(nk^{n-1})$ I/Os (where n is the number of dimensions, and k denotes the maximum number of pages covered in one dimension among all the n dimensions during a query). The practical efficiency of our technique is demonstrated with extensive experiments.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.1-13
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• 2007

The necessity of future index is increasing to predict the future location of moving objects promptly for various location-based services. A representative research topic related to future index is the probability trajectory prediction technique that improves reliability using the past trajectory information of moving objects in the road network environment. However, the prediction performance of this technique is lowered by the heavy load of extensive future trajectory search in long-range future queries, and its index maintenance cost is high due to the frequent update of future trajectory. Thus, this paper proposes the Probability Cell Trajectory-Tree (PCT-Tree), a cell-based future indexing technique for efficient long-range future location prediction. The PCT-Tree reduces the size of index by rebuilding the probability of extensive past trajectories in the unit of cell, and improves the prediction performance of long-range future queries. In addition, it predicts reliable future trajectories using information on past trajectories and, by doing so, minimizes the cost of communication resulting from errors in future trajectory prediction and the cost of index rebuilding for updating future trajectories. Through experiment, we proved the superiority of the PCT-Tree over existing indexing techniques in the performance of long-range future queries.

• Journal of KIISE:Databases
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• v.34 no.5
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• pp.420-436
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• 2007

The choice of an effective indexing method is crucial to guarantee the performance of the spatial join operator which is heavily used in geographical information systems. The $R^*$-tree based method is renowned as one of the most representative indexing methods. In this paper, we propose an efficient spatial join technique based on the DOT(Double Transformation) index, and compare it with the spatial Join technique based on the $R^*$-tree index. The DOT index transforms the MBR of an spatial object into a single numeric value using a space filling curve, and builds the $B^+$-tree from a set of numeric values transformed as such. The DOT index is possible to be employed as a primary index for spatial objects. The proposed spatial join technique exploits the regularities in the moving patterns of space filling curves to divide a query region into a set of maximal sub-regions within which space filling curves traverse without interruption. Such division reduces the number of spatial transformations required to perform the spatial join and thus improves the performance of join processing. The experiments with the data sets of various distributions and sizes revealed that the proposed join technique is up to three times faster than the spatial join method based on the $R^*$-tree index.

• Journal of KIISE:Databases
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• v.32 no.2
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• pp.129-141
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• 2005

Although spatio-temporal databases have received considerable attention recently, there has been little work on processing range sum queries on the historical records of moving objects despite their importance. Since to answer range sum queries, the direct access to a huge amount of data incurs prohibitive computation cost, materialization techniques based on existing index structures are recently suggested. A simple but effective solution is to apply the materialization technique to the MVR-tree known as the most efficient structure for window queries with spatio-temporal conditions. However, the MVR-tree has a difficulty in maintaining pre-aggregated results inside its internal nodes due to cyclic paths between nodes. Aggregate structures based on other index structures such as the HR-tree and the 3DR-tree do not provide satisfactory query performance. In this paper, we propose a new indexing technique called the Adaptive Partitioned Aggregate R-Tree (APART) and query processing algorithms to efficiently process range sum queries in many situations. Experimental results show that the performance of the APART is typically above 2 times better than existing aggregate structures in a wide range of scenarios.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.205-207
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• 2004

인터넷의 급속한 발전으로 인해 다양한 종류의 데이터들이 증가하게 되었으며 이러한 데이터의 표현과 데이터 교환을 위해 XML이 사실상의 표준으로 빠르게 자리 잡아 가고 있다. XML문서를 데이터로 저장 시 오랜 기간에 걸쳐서 성숙된 RDBMS를 사용하여 XML데이터를 RDBMS로 저장 시 발생할 수 있는 단편화 방지와 XML질의의 효과적인 질의 처리에 대한 많은 연구들이 제안되었다. 본 논문에서는 XML 문서를 관계형 데이터베이스 스키마로 저장 시 발생할 수 XML문서내의 엘리먼트의 관계에 대한 정보를 저장하기 위해서 추가적으로 발생하는 정보의 수를 줄이고 엘리먼트간의 관계를 효과적으로 저장할 수 있는 방법에 대해서 연구한다.

• Journal of Korean Library and Information Science Society
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• v.31 no.1
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• pp.229-258
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• 2000

The growth of digital image an video archives is increasing the need for tools that efficiently search through large amount of visual dta. Retrieval of visual data is important issue in multimedia database. We are using contented-based visual data retrieval method for efficient retrieval of visual data. In this paper, we introduced fundamental techniques using characteristic values of image data and indexing techniques required for content-based visual retrieval. In addition we introduced content-based visual retrieval system for use of digital library.

• The Journal of Information Technology and Database
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• v.3 no.2
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• pp.75-96
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• 1996

This study is intended to compare the effectiveness of the neural network inductive learning model with a vector space model in information retrieval. As a result, searches responding to incomplete queries in the neural network inductive learning model produced a higher precision and recall as compared with searches responding to complete queries in the vector space model. The results show that the hybrid methodology of integrating an inductive learning technique with the neural network model can help solve information retrieval problems that are the results of inconsistent indexing and incomplete queries--problems that have plagued information retrieval effectiveness.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.319-321
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• 2003

웹 상에서 제공되는 영화 서비스는 사용자에게 시간과 공간을 초월하여 서비스를 받을 수 있다는 매력을 가지고 있다. 이러한 영화 서비스는 대부분 동영상 전체 내용에 대해 사용자 연령별로 등급을 나누어 서비스되거나 무차별 서비스가 되고 있다. 본 논문에서는 비디오 인덱싱 기술과 필터링 기법을 접목하여 하나의 동영상을 각 장면의 내용에 따라 사용자 연령별 차별화 된 서비스를 함으로써 영화 동영상에 대한 활용도를 높일 수 있는 방법을 제안하였다.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.8
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• pp.606-610
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• 2004

A noble caption text detection and recognition algorithm using the temporal nature of video is proposed in this paper. A text registration technique is used to locate the temporal and spatial positions of captions in video from the accumulated frame difference information. Experimental results show that the proposed method is effective and robust. Also, a high processing speed is achieved since no time consuming operation is included.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.11c
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• pp.1399-1402
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• 2003

본 연구에서는 XML 데이타의 효율적인 검색을 위한 색인 모델을 제안한다. 제안한 색인 모델은 문서 계층상의 모든 레벨에서 내용 기반 질의, 구조 기반 질의와 같은 다양한 질의를 지원하기 위한 구조정보와 이를 이용한 색인 구조로 구성된다. 그리고 구조 검색을 지원하기 위해 새로운 구조정보 표현 방법을 제안한다. 또한 제안된 색인 모델에 지속성을 부여하기 위해 색인 모델을 디스크에 저장하는 방법을 제안하고 간단한 질의의 처리 과정을 설명한다.