• Title/Summary/Keyword: graph decomposition

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A Study on Visibility Graph Generating Model of Ada Program (Ada 프로그램의 Visibility Graph 생성모델에 관한 연구)

  • Jeong Jung-Yeong;Kim Hui-Ju;Yun Chang-Seop
    • Journal of the military operations research society of Korea
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    • v.16 no.2
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    • pp.56-74
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    • 1990
  • Programming-in-the-Large refers to software development environment and includes the organization and representation of a system structure, module decomposition, component dependence analysis, seperate compilation, subsystem and composition identification. The most intricate problem in this environment is the mastery of the structural complexity of large software systems. Ada programming language is tailored to the needs for building of large, integrated software systems from many program units. The visibility graph generating model presented in this paper transforms Ada source program into a visibility graph with nodes for program units and edges for visibility relations among program units. The system description in terms of program units and their visibility relations produced by this model can be utilized for some apects of Programming-in-the-Large environment and also assists designeers, programmers, integrators and maintainers in defining, understanding and exploring the structure of evolving software systems. The model designed and implemented in Ada programming language runs on PCs and will remain useful both in practice and as experimental tool.

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Integrating Transition-based and Graph-based Dependency Parsers using Dual Decomposition (Dual Decomposition을 이용한 전이기반 및 그래프 기반 의존 파서 통합 모델)

  • Min, Jin-Woo;Na, Seung-Hoon;Sin, Jong-Hun;Kim, Young-Kil
    • Annual Conference on Human and Language Technology
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    • 2019.10a
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    • pp.25-29
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    • 2019
  • 딥러닝을 이용한 한국어 의존 파싱은 전이 기반 방식과 그래프 기반 방식으로 나뉘어 연구되어 왔다. 전이 기반 방식은 입력 버퍼와 스택으로부터 자질을 추출하여 모델을 통해 액션을 결정하고 액션에 따라 파스트리를 생성해 나가는 상향식(Botton-Up)의 지역적 모델이고 그래프 기반 방식은 문장 내의 모든 단어에 대해 지배소, 의존소가 될 수 있는 점수를 딥러닝 모델을 통해 점수화하여 트리를 생성하는 전역적 모델이다. 본 논문에서는 Dual Decomposition을 이용하여 하이브리드 방식으로 전이 기반 파서와 그래프 기반 파서를 결합하는 방법을 제안하고 BERT 언어 모델을 반영하여 세종 데이터 셋에서 UAS 94.47%, LAS 92.58% 그리고 SPMRL '14 데이터 셋에서 UAS 94.74%, UAS 94.20%의 성능을 보여 기존 그래프 기반 파서의 성능을 더욱 개선하였다.

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Fast Sampling Set Selection Algorithm for Arbitrary Graph Signals (임의의 그래프신호를 위한 고속 샘플링 집합 선택 알고리즘)

  • Kim, Yoon-Hak
    • The Journal of the Korea institute of electronic communication sciences
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    • v.15 no.6
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    • pp.1023-1030
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    • 2020
  • We address the sampling set selection problem for arbitrary graph signals such that the original graph signal is reconstructed from the signal values on the nodes in the sampling set. We introduce a variation difference as a new indirect metric that measures the error of signal variations caused by sampling process without resorting to the eigen-decomposition which requires a huge computational cost. Instead of directly minimizing the reconstruction error, we propose a simple and fast greedy selection algorithm that minimizes the variation differences at each iteration and justify the proposed reasoning by showing that the principle used in the proposed process is similar to that in the previous novel technique. We run experiments to show that the proposed method yields a competitive reconstruction performance with a substantially reduced complexity for various graphs as compared with the previous selection methods.

A Study on Constructing the Multiple-Valued Logic Systems over Finite Fields using by the Decision Diagram (결정도(決定圖)에 기초(基礎)한 유한체상(有限體上)의 다치논리(多値論理)시스템구성(構成)에 관한 연구(硏究))

  • Park, Chun-Myoung
    • Journal of IKEEE
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    • v.3 no.2 s.5
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    • pp.295-304
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    • 1999
  • This paper presents a method of constructing the Multiple-Valued Logic Systems(MVLS) over Finite Fields(FF) using by Decision Diagram(DD) that is based on Graph Theory. The proposed method is as following. First, we derivate the Ordered Multiple-Valued Logic Decision Diagram(OMVLDD) based on the multiple-valued Shannon's expansion theorem and we execute function decomposition using by sub-graph. Next, we propose the variable selecting algorithm and simplification algorithm after apply the each isomorphism and reodering vertex. Also we propose MVLS design method.

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A Study on Integration of Process Planning and Scheduling Using AND/OR Graph (AND/OR 그래프를 이용한 공정계획과 일정계획의 통합에 관한 연구)

  • Kim, Ki-Dong;Jeong, Han-Il;Chung, Dae-Young;Park, Jin-Woo
    • Journal of Korean Institute of Industrial Engineers
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    • v.23 no.2
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    • pp.323-341
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    • 1997
  • Traditionally, the Process Planning problems and the Scheduling problems have been considered as independent ones. However, we can take much advantages by solving the two problems simultaneously. In this paper, we deal with the enlarged problem that takes into account both the process planning and the scheduling problems. And we present a solution algorithm for the problem assuming that the given process plan data is represented by AND/OR graph. A mathematical model(mixed ILP model) whose objective is the minimization of the makespan, is formulated. We found that we can get the optimal solutions of the small-size problems within reasonable time limits, but not the large-size problems. So we devised an algorithm based on the decomposition strategy to solve the large-scale problems (realistic problems) within practical time limits.

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Graph Neural Networks for Korean Dependency Parsing (Graph Neural Networks을 이용한 한국어 의존 구문 분석)

  • Min, Jin-Woo;Hong, Seung-Yean;Lee, Young-Hoon;Na, Seung-Hoon
    • Annual Conference on Human and Language Technology
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    • 2019.10a
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    • pp.537-539
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    • 2019
  • 구문 분석은 문장의 구조를 분석하는 자연어처리 분야로 그래프 기반 방법과 전이 기반 방법으로 나뉘어 연구되어 왔다. 본 논문에서는 그래프 기반 방식에서 높은 성능을 보이고 있는 Deep Biaffine 어텐션 모델에 별도의 High-Order 정보 추출 없이 Graph Neural Network(GNNs)을 이용하여 High-Order 정보를 학습할 수 있도록 확장한 Deep Biaffine 어텐션 GNNs을 적용하여 한국어 세종 구문 분석 셋에서 UAS : 94.44%, LAS : 92.55%의 성능을 달성하였으며 Dual Decomposition을 통해 전이 기반 한국어 구문 분석 모델과 결합하여 추가적인 성능 향상을 보였다.

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Minimizing Weighted Tardiness using Decomposition Method (분할법을 이용한 가중납기지연 최소화 문제)

  • Byeon, Eui-Seok;Hong, Sung-Wook
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.29 no.1
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    • pp.109-115
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    • 2006
  • Exact solutions for practical-size problems in job shop will be highly inefficient. Scheduling heuristics, therefore, are typically found in the literature. If we consider real-life situations such as machine breakdowns, the existing scheduling methods will be even more limited. Scheduling against due-dates addresses one of the most critical issues in modern manufacturing systems. In this paper, the method for weighted tardiness schedule using a graph theoretic decomposition heuristic is presented. It outstands the efficiency of computation as well as the robustness of the schedule.

XED: Model-based XML Editor Generator for Data-Centric XML Documents (XED: 데이타 중심 XML문서를 위한 모델 기반의 XML 편집기 생성 도구)

  • 최종명;유재우
    • Journal of KIISE:Software and Applications
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    • v.30 no.10
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    • pp.894-903
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    • 2003
  • Though XML is widely used, it is still hard for end users to write XML documents. A lot of XML documents are data-centric documents which have formal data format. Even novices can easily write the data-centric XML documents if they use form-based GUIs. In this paper, we introduce a new method for generating form-based XML editor for data-centric XML documents automatically and an XML editor generator called XED. The DTD consists of sequence, choice, and repetition, and this structure can be represented with Document Decomposition Graph(DDG). XED allows users to generate an XML editor by applying the presentation rules to DDG. It also permits users to modify generated editor through changing editor`s GUI properties with direct manipulation.

An Optimization of Representation of Boolean Functions Using OPKFDD (OPKFDD를 이용한 불리안 함수 표현의 최적화)

  • Jung, Mi-Gyoung;Lee, Hyuck;Lee, Guee-Sang
    • The Transactions of the Korea Information Processing Society
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    • v.6 no.3
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    • pp.781-791
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    • 1999
  • DD(Decision Diagrams) is an efficient operational data structure for an optimal expression of boolean functions. In a graph-based synthesis using DD, the goal of optimization decreases representation space for boolean functions. This paper represents boolean functions using OPKFDD(Ordered Pseudo-Kronecker Functional Decision Diagrams) for a graph-based synthesis and is based on the number of nodes as the criterion of DD size. For a property of OPKFDD that is able to select one of different decomposition types for each node, OPKFDD is variable in its size by the decomposition types selection of each node and input variable order. This paper proposes a method for generating OPKFDD efficiently from the current BDD(Binary Decision Diagram) Data structure and an algorithm for minimizing one. In the multiple output functions, the relations of each function affect the number of nodes of OPKFDD. Therefore this paper proposes a method to decide the input variable order considering the above cases. Experimental results of comparing with the current representation methods and the reordering methods for deciding input variable order are shown.

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