• 정보처리학회논문지A
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• 제8A권2호
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• pp.179-188
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• 2001

We analyze the property of candidate node set in the network graph, and propose an algorithm to decrease shortest path-finding computation time by using multiple dynamic-range queue(MDRQ) structure. This MDRQ structure is newly created for effective management of the candidate node set. The MDRQ algorithm is the shortest path-finding algorithm that varies range and size of queue to be used in managing candidate node set, in considering the properties that distribution of candidate node set is constant and size of candidate node set rapidly change. This algorithm belongs to label-correcting algorithm class. Nevertheless, because re-entering of candidate node can be decreased, the shortest path-finding computation time is noticeably decreased. Through the experiment, the MDRQ algorithm is same or superior to the other label-correcting algorithms in the graph which re-entering of candidate node didn’t frequently happened. Moreover the MDRQ algorithm is superior to the other label-correcting algorithms and is about 20 percent superior to the other label-setting algorithms in the graph which re-entering of candidate node frequently happened.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.267-271
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• 2005

The goal of data mining is to extract new and useful knowledge from large scale datasets. As the amount of available data grows explosively, it became vitally important to develop faster data mining algorithms for various types of data. Recently, an interest in developing data mining algorithms that operate on graphs has been increased. Especially, mining frequent patterns from structured data such as graphs has been concerned by many research groups. A graph is a highly adaptable representation scheme that used in many domains including chemistry, bioinformatics and physics. For example, the chemical structure of a given substance can be modelled by an undirected labelled graph in which each node corresponds to an atom and each edge corresponds to a chemical bond between atoms. Internet can also be modelled as a directed graph in which each node corresponds to an web site and each edge corresponds to a hypertext link between web sites. Notably in bioinformatics area, various kinds of newly discovered data such as gene regulation networks or protein interaction networks could be modelled as graphs. There have been a number of attempts to find useful knowledge from these graph structured data. One of the most powerful analysis tool for graph structured data is frequent subgraph analysis. Recurring patterns in graph data can provide incomparable insights into that graph data. However, to find recurring subgraphs is extremely expensive in computational side. At the core of the problem, there are two computationally challenging problems. 1) Subgraph isomorphism and 2) Enumeration of subgraphs. Problems related to the former are subgraph isomorphism problem (Is graph A contains graph B?) and graph isomorphism problem(Are two graphs A and B the same or not?). Even these simplified versions of the subgraph mining problem are known to be NP-complete or Polymorphism-complete and no polynomial time algorithm has been existed so far. The later is also a difficult problem. We should generate all of 2$^n$ subgraphs if there is no constraint where n is the number of vertices of the input graph. In order to find frequent subgraphs from larger graph database, it is essential to give appropriate constraint to the subgraphs to find. Most of the current approaches are focus on the frequencies of a subgraph: the higher the frequency of a graph is, the more attentions should be given to that graph. Recently, several algorithms which use level by level approaches to find frequent subgraphs have been developed. Some of the recently emerging applications suggest that other constraints such as connectivity also could be useful in mining subgraphs : more strongly connected parts of a graph are more informative. If we restrict the set of subgraphs to mine to more strongly connected parts, its computational complexity could be decreased significantly. In this paper, we present an efficient algorithm to mine frequent subgraphs that are more strongly connected. Experimental study shows that the algorithm is scaling to larger graphs which have more than ten thousand vertices.

• 한국HCI학회논문지
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• 제10권1호
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• pp.5-17
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• 2015

최근 다양한 공공데이터가 개방되고 있으며, 적절한 데이터 마이닝과 시각화 알고리즘을 통해 일반 시민에게 서비스 되고 있다. 이를 통해 정부와 지방자치단체는 공공 정책의 투명성과 효율성을 널리 알릴 수 있을 뿐 아니라, 일반 사용자들이 개방된 공공데이터를 재가공하여 서비스함으로써 관련 산업의 성장을 이끌고 있다. 공공데이터의 최종 사용자는 일반 시민이기 때문에, 누구나 손쉽게 이해할 수 있도록 공공데이터를 적절히 시각화하는 것이 무엇보다 중요하다. 본 연구에서는 공공데이터 비주얼라이제이션의 중요성을 널리 알리기 위해, 일반 국민이 관심을 가질만한 공공데이터로 UN 회원국의 투표 데이터를 고려한다. 외교와 교육 목적으로 그 활용 가치가 높고 데이터를 쉽게 얻을 수 있는 장점이 있다. 또한 적절한 데이터 마이닝과 시각화 과정을 거친다면, 일반 사용자들이 유엔 회원국 간의 투표 성향에 대한 통찰력을 쉽게 얻을 수 있다. 유엔 투표 데이터를 시각화하기 위해서는, 회원국 간의 투표성향 유사도를 측정하고, 이를 바탕으로 소셜 그래프를 구현한다. 그리고 그래프 레이아웃 알고리즘을 적용하여 그래프를 화면에 렌더링 하게 된다. 기존 방법을 이용하여 소셜 그래프를 비주얼라이제이션 할 경우에 그래프의 복잡도가 증가하여 유엔 회원국 간의 투표성향을 파악하는데 큰 어려움이 있다. 이러한 문제를 개선하기 위해, 본 논문에서는 친구 매칭(Friend-Matching), 친구-라이벌 매칭(Friend-Rival Matching), 버블힙(Bubble Heap) 알고리즘들을 차례로 제안한 다. 제안된 알고리즘을 바탕으로, 기존 그래프 비주얼라이제이션을 개선하여 일반 사용자들이 손쉽게 유엔 회원국 간의 투표성향과 관련된 특정 패턴이나 통찰력을 얻는데 큰 도움을 줄 것이다. 또한 웹에서 동작하는 프로토타입을 구현하여, 누구나 방문하여 테스트를 할 수 있다. 웹 페이지 주소: http://datalab.kunsan.ac.kr/politiz/un/

• 정보교육학회논문지
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• 제2권2호
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• pp.269-277
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• 1998

분산처리 시스템하에서 교착 상태를 발견하기 위한 대부분의 분산 알고리즘은 probe라는 짧은 메시지를 사용하지만 발생되는 메시지의 일부분만이 사용될 뿐이다. 따라서 불필요한 probe들은 communication traffic을 심히 초래하는 결과를 낳는다. 본 논문에서는 이러한 결점을 보완하여 모든 probe들 이 유효하게 사용되어지는 알고리즘을 제시한다. Wait-for-graph상의 모든 edge의 수를 e라고 하였을 때, 제시된 알고리즘은 graph 상의 모든 교착 상태를 O(e) 메시지를 사용하여 발견한다.

• 한국정보처리학회논문지
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• 제7권7호
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• pp.2060-2071
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• 2000

Scheduling parallel tasks, represented as a Directed Acyclic Graph (DAG) or task graph, on a multiprocessor system has been an important research area in the past decades. List scheduling algorithms assign priorities to a node or an edge in an input DAG, and then generate a schedule according to the assigned priorities. This appear proposes a list scheduling algorithms with effective method of priority assignments. The paper also analyzes the worst case performance and optimality condition for the proposed algorithm. The performance comparison study shows that the proposed algorithms outperforms existing scheduling algorithms especially for input DAGs with high communication overheads. The performance improvement over existing algorithms becomes larger as the input DAG becomes more dense and the level of parallelism in the DAG is increased.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.800-807
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• 2022

This study aims to review the use of graph databases in construction research. Based on the diagnosis of the current research status, a future research direction is proposed. The use of graph databases in construction research has been increasing because of the efficiency in expressing complex relations between entities in construction big data. However, no study has been conducted to review systematically the status quo of graph databases. This study analyzes 42 papers in total that deployed a graph model and graph database in construction research, both quantitatively and qualitatively. A keyword analysis, topic modeling, and qualitative content analysis were conducted. The review identified the research topics, types of data sources that compose a graph, and the graph database application methods and algorithms. Although the current research is still in a nascent stage, the graph database research has great potential to develop into an advanced stage, fused with artificial intelligence (AI) in the future, based on the active usage trends this study revealed.

• Journal of applied mathematics & informatics
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• 제28권5_6호
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• pp.1347-1358
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• 2010

An upright drawing of a planar graph G on k layers is a planar straight-line drawing of G, where the vertices of G are placed on a set of k horizontal lines, called layers and no two adjacent vertices are placed on the same layer. There is a previously known algorithm that decides in linear time whether a planar graph admits an upright drawing on k layers for a fixed value of k. However, the constant factor in the running time of the algorithm increases exponentially with k and makes it impractical even for k = 3. In this paper, we give a linear-time algorithm to examine whether a biconnected planar graph G admits an upright drawing on three layers and to obtain such a drawing if it exists. We also give a necessary and sufficient condition for a tree to have an upright drawing on three layers. Our algorithms in both the cases are much simpler and easier to implement than the previously known algorithms.

• 한국멀티미디어학회논문지
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• 제17권6호
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• pp.716-724
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• 2014

The pancake graph is node symmetric and is utilized on the data sorting algorithm. We propose a new half pancake graph that improve pancake graph's network cost. The half pancake degree is approximately half of pancakes degree and diameter is 3n+4. The pancake graph's network cost is $O(1.64n^2)$ and half pancake's is $O(1.5n^2)$. Additionally half pancake graph is sub graph of pancake graph. As this result, The several algorithms developed in pancake graph has the advantage of leverage on the pancake by adding constant cost.

• 한국멀티미디어학회논문지
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• 제17권6호
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• pp.725-732
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• 2014

The Pancake graph is node symmetric and useful interconnection network in the field of data sorting algorithm. The Half Pancake graph is a new interconnection network that reduces the degree of the Pancake graph by approximately half and improves the network cost of the Pancake graph. In this paper, we analyze topological properties of the Half Pancake graph $HP_n$. Fist, we prove that $HP_n$ has maximally fault tolerance and recursive scalability. In addition, we show that in $HP_n$, there are isomorphic graphs of low-dimensional $HP_n$. Also, we propose that the Bubblesort $B_n$ can be embedded into Half Pancake $HP_n$ with dilation 5, expansion 1. These results mean that various algorithms designed for the Pancake graph and the Bubble sort graph can be executed on $HP_n$ efficiently.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2004년도 춘계공동학술대회 논문집
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• pp.718-721
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• 2004

This paper introduces a novel method of partitioning a cyclic workflow graph into the subgraphs of acyclic flows. The way of iterative classification of nodes according to feedback structures and deriving subgraphs of acyclic flows is described with illustrative examples. The proposed method allows a cyclic workflow model to be analyzed further, if necessary, with several smaller subflows, which are all acyclic.