• Title/Summary/Keyword: influence graph

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A Gradient-Based Explanation Method for Node Classification Using Graph Convolutional Networks

  • Chaehyeon Kim;Hyewon Ryu;Ki Yong Lee
    • Journal of Information Processing Systems
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    • v.19 no.6
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    • pp.803-816
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    • 2023
  • Explainable artificial intelligence is a method that explains how a complex model (e.g., a deep neural network) yields its output from a given input. Recently, graph-type data have been widely used in various fields, and diverse graph neural networks (GNNs) have been developed for graph-type data. However, methods to explain the behavior of GNNs have not been studied much, and only a limited understanding of GNNs is currently available. Therefore, in this paper, we propose an explanation method for node classification using graph convolutional networks (GCNs), which is a representative type of GNN. The proposed method finds out which features of each node have the greatest influence on the classification of that node using GCN. The proposed method identifies influential features by backtracking the layers of the GCN from the output layer to the input layer using the gradients. The experimental results on both synthetic and real datasets demonstrate that the proposed explanation method accurately identifies the features of each node that have the greatest influence on its classification.

Graphical Methods for Evaluating the Effect of Outliers in Univariate and Bivariate Data (일변량 및 이변량 자료에 대하여 특이값의 영향을 평가하기 위한 그래픽 방법)

  • Jang, Dae-Heung
    • Proceedings of the Korean Society for Quality Management Conference
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    • 2006.11a
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    • pp.221-226
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    • 2006
  • We usually use two techniques(influence function and local influence) for detecting outliers. But, we cannot use these difficult techniques in elementary industrial statistics course for college students. We can use some simple graphical methods(box plot, dandelion seed plot, influence graph and cumulative deletion plot) for univariate and bivariate outlier detection and outlier effect in elementary industrial statistics course for college students.

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A Study on the Teaching of 'Function' utilizing the Graph Art - Case study focusing on the activities of Ulsan WISE Science Camp - (Graph Art를 활용한 함수 지도에 관한 연구 - 울산 WISE 과학캠프활동을 중심으로 한 사례연구 -)

  • Chung, Young-Woo;Kim, Boo-Yoon
    • The Mathematical Education
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    • v.51 no.3
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    • pp.197-210
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    • 2012
  • In this study, we will develop and implement the teaching program of 'Function', on the subject of "Poster-Making utilizing the Graph Art" in the Math Camp for middle-school students. And we will examine the didactical significance through student's activities and products. The teaching program of 'Function' utilizing the Graph Art can be promoted self-directly the understanding of 'Function' concept and the ability for handling 'Function'. In the process of drawing up the graph art, in particular, this program help students to promote the ability for problem-solving and mathematical thinking, and to communicate mathematically and attain the his own level. Ultimately, this program have a positive influence upon cognitive and affective and areas with regard to mathematics.

Spectral Clustering with Sparse Graph Construction Based on Markov Random Walk

  • Cao, Jiangzhong;Chen, Pei;Ling, Bingo Wing-Kuen;Yang, Zhijing;Dai, Qingyun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.7
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    • pp.2568-2584
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    • 2015
  • Spectral clustering has become one of the most popular clustering approaches in recent years. Similarity graph constructed on the data is one of the key factors that influence the performance of spectral clustering. However, the similarity graphs constructed by existing methods usually contain some unreliable edges. To construct reliable similarity graph for spectral clustering, an efficient method based on Markov random walk (MRW) is proposed in this paper. In the proposed method, theMRW model is defined on the raw k-NN graph and the neighbors of each sample are determined by the probability of the MRW. Since the high order transition probabilities carry complex relationships among data, the neighbors in the graph determined by our proposed method are more reliable than those of the existing methods. Experiments are performed on the synthetic and real-world datasets for performance evaluation and comparison. The results show that the graph obtained by our proposed method reflects the structure of the data better than those of the state-of-the-art methods and can effectively improve the performance of spectral clustering.

Stability Assessment of Underground Limestone Mine Openings by Stability Graph Method (Stability graph method에 의한 석회석 지하채굴 공동의 안정성 평가)

  • Sunwoo Choon;Jung Yong-Bok
    • Tunnel and Underground Space
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    • v.15 no.5 s.58
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    • pp.369-377
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    • 2005
  • The stability of underground openings is a major concern for the safety and productivity of mining operations. Rock mass classification methods provide the basis of many empirical design methods as well as a basis for numerical analysis. Of the many factors which influence the stability of openings, the span of the opening for a given rock mass condition provides an important parameter of design. In this paper, the critical span curves proposed by Lang, the Mathews stability graph method and the modified critical span curve suggested by the authors have been assessed. The modified critical span curve was proposed by using Mathews stability graph method. The modified critical span curve by the author have been used to assess the stability of underground openings in several limestone mines.

-An Implementation of a Graph-based Modeling System using Influence Diagram- (영향도를 이용한 그래프 기반 모델링 시스템의 응용)

  • 박동진;황인극
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.23 no.55
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    • pp.85-96
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    • 2000
  • This paper describes IDMS, a graph-based modeling system that supports problem structuring. We employs influence diagram as a problem representation tool, that is, a modeling tool. In particular, IDMS is designed as domain-independent shell. Therefore, a modeler can change the contents of the knowledge base to suit his/her own interested domain. Since the knowledge base of IDMS contains both modeling knowledge and domain knowledge, IDMS provides not only the syntactic support for modeling tool, but also the semantic support for problem domain. To apply the method in the real world context, we tested IDMS on the process selection problem in business reengineering, which is typical semi-structured problem.

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A Horizontal Partition of the Object-Oriented Database for Efficient Clustering

  • Chung, Chin-Wan;Kim, Chang-Ryong;Lee, Ju-Hong
    • Journal of Electrical Engineering and information Science
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    • v.1 no.1
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    • pp.164-172
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    • 1996
  • The partitioning of related objects should be performed before clustering for an efficient access in object-oriented databases. In this paper, a horizontal partition of related objects in object-oriented databases is presented. All subclass nodes in a class inheritance hierarchy of a schema graph are shrunk to a class node in the graph that is called condensed schema graph because the aggregation hierarchy has more influence on the partition than the class inheritance hierarchy. A set function and an accessibility function are defined to find a maximal subset of related objects among the set of objects in a class. A set function maps a subset of the domain class objects to a subset of the range class objects. An accessibility function maps a subset of the objects of a class into a subset of the objects of the same class through a composition of set functions. The algorithm derived in this paper is to find the related objects of a condensed schema graph using accessibility functions and set functions. The existence of a maximal subset of the related objects in a class is proved to show the validity of the partition algorithm using the accessibility function.

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A Study on the Guidance Signage System of Outpatient in General Hospital using Spatial Configuration Theory - View from G.D.Weisman's Way-finding Influence Factors (공간구조론을 적용한 종합병원 외래부 유도사인 배치 및 평가에 관한 연구 - G.D.Weisman의 길찾기 요소를 중심으로)

  • Kim, Suktae;Paik, Jinkyung
    • Journal of The Korea Institute of Healthcare Architecture
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    • v.21 no.3
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    • pp.25-35
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    • 2015
  • Purpose: Signs that are installed at unnoticeable places or that disconnect before the destination can bring errors of location information delivery. Therefore, this study aims to find out the spatial relation between structure of space and signs in the perspective of visual exposure possibility, operating arrangement and assesment by applying spatial structure theory. Methods: Effectiveness of organization of guidance signs was evaluated after the four way-finding factors(Plan Configuration, Sign System, Perceptual Access, Architectural Difference) that G.D.Weisman suggested were interpreted by spatial structure theory(J-Graph analysis, Space Syntax, Visual Graph Analysis) under the premise that it is closely related to the structure of space. Results: 1) Because the south corridor that connects each department of outpatient division is located in the hierarchy center of the space, and walking density is expected to be high, guidance signs need to be organized at the place with high integration value. 2) The depth to the destination space can be estimated through J-Graph analysis. The depth means a switch of direction, and the guidance signs are needed according to the number. 3) According to visibility graph analysis, visual exposure can be different in the same hierarchy unit space according to the shape of the flat surface. Based on these data, location adjustment of signs is possible, and the improvement effect can be estimated quantitatively. Implications: Spatial structure theory can be utilized to design and evaluate sign systems, and it helps to clearly understand the improvement effect. It is desirable to specify design and estimation of sign systems in the order of J-Graph analysis${\rightarrow}$Space Syntax Theory${\rightarrow}$visibility graph analysis.

Finger Detection using a Distance Graph (거리 그래프를 이용한 손가락 검출)

  • Song, Ji-woo;Oh, Jeong-su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.10
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    • pp.1967-1972
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    • 2016
  • This paper defines a distance graph for a hand region in a depth image and proposes an algorithm detecting finger using it. The distance graph is a graph expressing the hand contour with angles and Euclidean distances between the center of palm and the hand contour. Since the distance graph has local maximum at fingertips' position, we can detect finger points and recognize the number of them. The hand contours are always divided into 360 angles and the angles are aligned with the center of the wrist as a starting point. And then the proposed algorithm can well detect fingers without influence of the size and orientation of the hand. Under some limited recognition test conditions, the recognition test's results show that the recognition rate is 100% under 1~3 fingers and 98% under 4~5 fingers and that the failure case can also be recognized by simple conditions to be available to add.

The Effects of MBL-Used Instruction on Scientific Inquiry Skill and Graph Construction and Interpreting Abilities of Middle School Students (MBL 활용 수업이 중학교 학생들의 과학탐구능력과 그래프 작성 및 해석능력에 미치는 효과)

  • Choi, Sung-Bong
    • Journal of the Korean earth science society
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    • v.29 no.6
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    • pp.487-494
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    • 2008
  • The purpose of this study was to investigate the effects of MBL experiment instruction on the 7th graders' scientific inquiry skills and graph construction and interpretation ability in the unit "Elements and movement of sea water". Results are as follows: First, this study analyzed the influence on students' scientific inquiry skill after having six MBL instructional classes. The result showed a significant difference in the scientific inquiry skills between the experimental group and the control group, which implies that the instruction using MBL was an effective way to improve students' scientific inquiry skills. Second, this study also analyzed the influence on students' abilities to construct and interpret graphs. The result did not show any significant differences between the experimental group and the control group in the ability to construct graphs. But it showed significant differences in the ability to interpretgraphs, which means that instruction using MBL was an effective way to improve students' ability to interpret graphs.