• Journal of Platform Technology
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• v.9 no.4
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• pp.3-9
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• 2021

In this paper, a graph data model is introduced to effectively recognize the situation between each object on the road detected by vehicles or road infrastructure sensors. The proposed method builds a graph database by modeling each object on the road as a node of the graph and the relationship between objects as an edge of the graph, and updates object properties and edge properties in real time. In this case, the relationship between objects represented as edges is set when there is a possibility of approach between objects in consideration of the position, direction, and speed of each object. Finally, we propose a spatial indexing technique for graph nodes and edges to update the road object graph database represented through the proposed graph modeling method continuously in real time. To show the superiority of the proposed indexing technique, we compare the proposed indexing based database update method to the non-indexing update method through simulation. The results of the simulation show the proposed method outperforms more than 10 times to the non-indexing method.

• Journal of KIISE:Software and Applications
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• v.26 no.9
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• pp.1039-1051
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• 1999

시공간 데이타베이스는 현실세계의 객체에 대하여 효율적인 공간 관리와 이력 관리를 지원한다. 이러한 시공간 데이타베이스는 시간차원과 공간차원이라는 이질적 데이타 공간을 관리하여야 하는 대단히 복잡한 시스템이다. 따라서 데이타에 대한 효율적 접근 방법에 대한 연구가 필수적이며, 이는 효율적 색인 기법의 개발을 통하여 이룰 수 있다. 그러나 시공간 데이타에 대한 접근방법 연구는 거의 이루어지지 않고 있으며 극소수의 사례들마저도 공간 객체의 이력 개념을 지원하는 것이 아니라 멀티미디어 객체의 상대적 시간만을 지원하고 있다. 따라서 이 논문에서는 공간 데이타의 이력을 표현하는 시공간 데이타에 대하여 효율적으로 색인하기 위한 방안으로서 시간과 공간을 단일화된 색인 영역으로 통합하는 단일화된 시공간 색인 모델을 제시하고, 이를 기존의 R-트리를 기반으로 확장한 색인을 설계 및 구현하였으며, 아울러 다양한 유형의 시공간 연산에 대한 색인의 성능을 평가하였다.Abstract Spatiotemporal databases are able to support an efficient spatial management as well as historical management for an object in the real world. It is very complex to manage these two dimensions why there exists on difference of inborn property of temporal and spatial dimensions. Therefore an efficient access method should be studied, and it can be done by means of development of efficient indexing technology.However, there is a few related work in the research of access methods of spatiotemporal data. Also the previous works do not support the concept of history for spatial object, and only support the relative time among multimedia objects. Therefore, in this paper, we propose a unified Spatiotemporal index model as an efficient index for Spatiotemporal data. And we not only design Spatiotemporal index that has been extended to historical management facility on the basis of conventional R-tree, but also implement it. Finally we have evaluated performance of index for the various kinds of Spatiotemporal operations.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2327-2340
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• 2000

Existing bulk loading algorithms for multi-dimensional index structures suffer from satisfying both index construction time and retrieval perfonnancc. In this paper, we propose an efficient bulk loading algorithm to construct high dimensional index structures for large data set that overcomes the problem. Although several bulk loading algorithms have been proposed for this purpose, none of them improve both constnlCtion time and search performance. To improve the construction time, we don't sort whole data set and use bisectiou algorithm that divides the whole data set or a subset into two partitions according to the specific pivot value. Also, we improve the search performance by selecting split positions according to the distribution properties of the data set. We show that the proposed algorithm is superior to existing algorithms in terms of construction time and search perfomlance through various experiments.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.128-137
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• 2002

In this paper, we propose the LPC+-file for efficient indexing of high-dimensional image data. With the proliferation of multimedia data, there Is an increasing need to support the indexing and retrieval of high-dimensional image data. Recently, the LPC-file (5) that based on vector approximation has been developed for indexing high-dimensional data. The LPC-file gives good performance especially when the dataset is uniformly distributed. However, compared with for the uniformly distributed dataset, its performance degrades when the dataset is clustered. We improve the performance of the LPC-file for the strongly clustered image dataset. The basic idea is to adaptively partition the data space to find subspaces with high-density clusters and to assign more bits to them than others to increase the discriminatory power of the approximation of vectors. The total number of bits used to represent vector approximations is rather less than that of the LPC-file since the partitioned cells in the LPC+-file share the bits. An empirical evaluation shows that the LPC+-file results in significant performance improvements for real image data sets which are strongly clustered.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.56-68
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• 2006

For tracing tag locations, the trajectories should be modeled and indexed in radio frequency identification (RFID) systems. The trajectory of a tag can be represented as a line that connects two spatiotemporal locations captured when the tag enters and leaves the vicinity of a reader. If a tag enters but does not leave a reader, its trajectory is represented only as a point captured at entry. Because the information that a tag stays in a reader is missing from the trajectory represented only as a point, it is impossible to find the tag that remains in a reader. To solve this problem we propose the data model in which trajectories are defined as time-parameterized intervals and new index scheme called the Time Parameterized Interval R-tree. We also propose new insert and split algorithms that reduce the area of nodes to enable efficient query processing. We evaluate the performance of the proposed index scheme and compare it with previous indexes on various datasets.

• Journal of KIISE:Software and Applications
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• v.26 no.1
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• pp.52-65
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• 1999

이미지나 비디오, 오디오와 같이 멀티미디어 데이터들은 기존의 단순한 텍스트 기반의 데이터에 비하여 대용량적인 특성과 비정형적인 특성을 가지고 있어서 검색시 많은 어려움이 따른다. 본 논문에서는 대규모의 이미지 데이터베이스에서 효율적이고 신속하게 사용자가 원하는 이미지를 검색할수 있는 내용 기반 검색 시스템을 제시한다. 이를 위해서 본 논문에서는 최근 여러 장점으로 인하여 신호 분석이나 이미지 압축 분야에 많이 사용되는 웨이브릿 변환을 이용하여 이미지 데이터로부터 내용 기반 검색에 사용되는 특징 벡터를 효율적으로 추출하는 기법과 유사성 측정 방법을 제안한다. 그리고, 이러한 특징 추출방법과 유사성 측정 방법을 이용하여 내용 기반 질의 및 검색을 수행할 경우, 검색 조건을 만족하는 객체인데 실수로 검색해내지 못하는 경우인 false dismissals 이 발생하지 않음을 보인다. 또한 대규모 이미지 데이터베이스에서 신속한 내용 기반 검색을 지원하기 위하여 고차원 데이터에 대한 효율적인 색인을 제공하는 X-tree를 이용한 이미지 색인 방법을 보이며 이것이 기존의 순차 검색이나 R*-tree를 이용한 색인 방법보다 신속하게 이미지 데이터들을 검색할 수 있다는 것을 다양한 실험을 통해 보인다. 마지막으로 QBIC에서 제안한 검색 적합성 측정 방법을 이용하여 본 논문에서 제안하는 내용 기반 이미지 검색시스템의 검색 적합성을 보인다.

• 한국공간정보시스템학회:학술대회논문집
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• 2003.11a
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• pp.141-146
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• 2003

시간이 흐름에 따라 연속적으로 위치를 변경하는 객체를 이동 객체(Moving Objects)라고 한다. 이러한 이동 객체의 대용량 위치 정보를 효율적으로 검색하기 위하여 색인이 필요하며, 대표적인 색인으로 TB-tree가 제안되었다. 그러나 전통적인 R-tree 기반의 TB-tree는 엄격한 궤적 보존 정책에 의해 레코드가 삽입될 때마다 해당 레코드의 선행자(predecessor)를 포함하는 단말 노드를 검색해야 하며, 레코드 삽입으로 인한 단말 노드 MBB의 변경을 중간 노드들의 MBB에도 반영해야 하는 갱신 부하를 가지고 있다. 본 논문에서는 대용량 이동 객체 궤적 정보의 효율적인 색인을 위한 최소 전파 TB-tree를 제안한다. 본 기법은 앞으로 삽입될 이동 객체의 궤적을 포함하는 예상된 MBB(EMBB: Expected Minimum Bounding Box)를 트리에 먼저 반영한 후 레코드가 삽입될 때마다 중간 노드의 MBB를 갱신하지 않고, 객체가 EMBB을 벗어났을 때 중간 노드의 MBB를 조정하여 TB-tree의 MBB조정 횟수를 줄이고, 또한 TB-tree에 별도의 테이블 구조를 둠으로써 레코드 삽입을 위한 단말 노드 검색 비용을 줄여 전체적인 TB-tree의 갱신 비용을 감소시킨다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.1
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• pp.44-48
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• 2004

This paper proposes a phrase-based indexing system based on the phrase. the larger syntax unit than a single keyword. Early information retrieval systems with indexing system matching single keyword is simple and popular. But with single keyword matching it is very hard to represent the exact meaning of documents and the set of documents from retrieval is very large, therefore it can't satisfy the user of the information retrieval systems. Web documents include lots of syntactic errors, the natural language parser with high quality cannot be expected in Web. Partial trees, even not a full tree, from fully bottom-up parsing is still useful for extracting phrases, and they are much more discriminative than single keyword for index. It helps the information retrieval system enhance the efficiency and reduce the processing overhead, too.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.710-720
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• 2004

As XML documents have much richer information than plain texts, we can perform very elaborated, fine-grained search which was difficult in past years. However, as the cost of finer grained element level search is very high, the processing overhead has become a new challenge. We propose an inverted index structure called PIX, which reduces the number of elements processed by partitioning elements according to their match potentiality. We choose a base level and partition elements according to whether they have possibility of having a common ancestor higher than the level. We also propose partition merging technique by which we can get same results as unpartitioned case. Our experimental results show that the index partitioning strategy can reduce processing time considerably.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.689-700
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• 2002

In this paper, we developed Korean Morphological Analyzer for an automatic indexing that is essential for Information Retrieval. Since it is important to index large-scaled document set efficiently, we concentrated on maximizing the speed of word analysis, modularization and structuralization of the system without new concepts or ideas. In this respect, our system is characterized in terms of software engineering aspect to be used in real world rather than theoretical issues. First, a dictionary of words was structured. Then modules that analyze substantive words and inflected words were introduced. Furthermore numeral analyzer was developed. And we introduced an unknown word analyzer using the patterns of morpheme. This whole system was integrated into K-2000, an information retrieval system.