• Title, Summary, Keyword: Concept Graph

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On the Organization of Object-Oriented Model Bases for Structured Modeling (구조적 모델링을 위한 객체지향적 모델베이스 조직화)

  • 정대율
    • The Journal of Information Systems
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    • v.5
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    • pp.149-173
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    • 1996
  • This paper focus on the development of object-oriented model bases for Structured Modeling. For the model base organization, object modeling techniques and model typing concept which is similar to data typing concept are used. Structured modeling formalizes the notion of a definitional system as a way of dscribing models. From the object-oriented concept, a structured model can be represented as follows. Each group of similar elements(genus) is represented by a composite class. Other type of genera can be represented in a similar manner. This hierarchical class composition gives rise to an acyclic class-composition graph which corresponds with the genus graph of structured model. Nodes in this graph are instantiated to represent the elemental graph for a specific model. Taking this class composition process one step further, we aggregate the classes into higher-level composite classes which would correspond to the structured modeling notion of a module. Finally, the model itself is then represented by a composite class having attributes each of whose domain is a composite class representing one of the modules. The resulting class-composition graph represent the modular tree of the structured.

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CHARACTERIZATION THEOREMS FOR CERTAIN CLASSES OF INFINITE GRAPHS

  • Jung, Hwan-Ok
    • Journal of applied mathematics & informatics
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    • v.30 no.1_2
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    • pp.245-252
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    • 2012
  • In this paper we present a necessary and sufficient conditions for an infinite VAP-free plane graph to be a 3LV-graph as well as an LV-graph. We also introduce and investigate the concept of the order and the kernel of an infinite connected graph containing no one-way infinite path.

Mining Highly Reliable Dense Subgraphs from Uncertain Graphs

  • LU, Yihong;HUANG, Ruizhi;HUANG, Decai
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.6
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    • pp.2986-2999
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    • 2019
  • The uncertainties of the uncertain graph make the traditional definition and algorithms on mining dense graph for certain graph not applicable. The subgraph obtained by maximizing expected density from an uncertain graph always has many low edge-probability data, which makes it low reliable and low expected edge density. Based on the concept of ${\beta}$-subgraph, to overcome the low reliability of the densest subgraph, the concept of optimal ${\beta}$-subgraph is proposed. An efficient greedy algorithm is also developed to find the optimal ${\beta}$-subgraph. Simulation experiments of multiple sets of datasets show that the average edge-possibility of optimal ${\beta}$-subgraph is improved by nearly 40%, and the expected edge density reaches 0.9 on average. The parameter ${\beta}$ is scalable and applicable to multiple scenarios.

A Study Nuenal Model of Concept Retrieval (개념 검색의 신경회로망 모델에 관한 연구)

  • Kauh, Yong-Hoon;Park, Sang-Hui
    • Proceedings of the KIEE Conference
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    • pp.450-456
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    • 1990
  • In this paper, production system is implemented with the inferential neural network model using semantic network and directed graph. Production system can be implemented with the transform of knowledge representation in production system into semantic network and of semantic network into directed graph, because directed graphs can be expressed by neural matrices. A concept node should be defined by the state vector to calculated the concepts expressed by matrices. The expressional ability of neunal network depends on how the state vector is defined. In this study, state vector is overlapped and each overlapping part acts as a inheritant of concept.

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Similarity Evaluation between Graphs: A Formal Concept Analysis Approach

  • Hao, Fei;Sim, Dae-Soo;Park, Doo-Soon;Seo, Hyung-Seok
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1158-1167
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    • 2017
  • Many real-world applications information are organized and represented with graph structure which is often used for representing various ubiquitous networks, such as World Wide Web, social networks, and protein-protein interactive networks. In particular, similarity evaluation between graphs is a challenging issue in many fields such as graph searching, pattern discovery, neuroscience, chemical compounds exploration and so forth. There exist some algorithms which are based on vertices or edges properties, are proposed for addressing this issue. However, these algorithms do not take both vertices and edges similarities into account. Towards this end, this paper pioneers a novel approach for similarity evaluation between graphs based on formal concept analysis. The feature of this approach is able to characterize the relationships between nodes and further reveal the similarity between graphs. Therefore, the highlight of our approach is to take vertices and edges into account simultaneously. The proposed algorithm is evaluated using a case study for validating the effectiveness of the proposed approach on detecting and measuring the similarity between graphs.

A Design of Traverse and Representation Method of Maze for Shortest Path Search with Robots (로봇의 최단경로탐색을 위한 미로의 순회 및 표현방법 설계)

  • Hong, Ki-Cheon
    • 한국정보교육학회:학술대회논문집
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    • pp.227-233
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    • 2010
  • Graph is applied to GIS, Network, AI and so on. We use graph concept in our daily life unconsciously. So this paper describe how graph concept is used when robot searches shortest path between two distinct vertices. It is performed in real world. For this, it consists of three step; maze traverse, graph generation, and shortest path search. Maze traverse steps is that robot navigates maze. It is most difficult step. Graph generation step is to represent structural information into graph. Shortest path search step is to that robot move between two vertices. It is not implemented yet. So we introduce process in design level.

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KG_VCR: A Visual Commonsense Reasoning Model Using Knowledge Graph (KG_VCR: 지식 그래프를 이용하는 영상 기반 상식 추론 모델)

  • Lee, JaeYun;Kim, Incheol
    • KIPS Transactions on Software and Data Engineering
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    • v.9 no.3
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    • pp.91-100
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    • 2020
  • Unlike the existing Visual Question Answering(VQA) problems, the new Visual Commonsense Reasoning(VCR) problems require deep common sense reasoning for answering questions: recognizing specific relationship between two objects in the image, presenting the rationale of the answer. In this paper, we propose a novel deep neural network model, KG_VCR, for VCR problems. In addition to make use of visual relations and contextual information between objects extracted from input data (images, natural language questions, and response lists), the KG_VCR also utilizes commonsense knowledge embedding extracted from an external knowledge base called ConceptNet. Specifically the proposed model employs a Graph Convolutional Neural Network(GCN) module to obtain commonsense knowledge embedding from the retrieved ConceptNet knowledge graph. By conducting a series of experiments with the VCR benchmark dataset, we show that the proposed KG_VCR model outperforms both the state of the art(SOTA) VQA model and the R2C VCR model.

The Effect on Forming Functional Concept by Teaching Function Based on Variable (변수에 의한 함수 지도가 함수개념의 형성에 미치는 효과)

  • 이덕호;길영순
    • Journal of the Korean School Mathematics Society
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    • v.4 no.1
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    • pp.103-114
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    • 2001
  • The purpose of this study is to develop learning materials for functional concept on variable and to verify the effect of how well students could learn functional concept after they studied with those materials. To accomplish the purpose of this study, I developed learning materials and after teaching students with them. I have concluded the followings : First, there was little effect in teaching functional concept on variable between two experimental groups, whereas teaching functional concept had greater effect on forming functional concept in high level groups in those two experimental groups. Second, teaching functional concept on variable had little effect on students' understanding of functional concept and perfecting tables in Black box, graph, and mathematical problems, whereas there was much effect in students' understanding functional concept and solving relation formula, image, and range problems related to everyday life or general things. On the basis of the problems which appeared in the process of this study, the following can be suggested : First, we should develop learning materials fit for low level students so that they could understand functional concept. Second, we should continue to teach the basic problems like solving relation formula, image, and range, and understanding functional concept in graph until students are able to understand them exactly. Third, since the goals of Unit Function in a middle school textbook is to solve problems related to everyday life through functional thinking, there should be change in constructing systematic contents of Unit Function in a middle school textbook.

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Conceptual Graph Matching Method for Reading Comprehension Tests

  • Zhang, Zhi-Chang;Zhang, Yu;Liu, Ting;Li, Sheng
    • Journal of information and communication convergence engineering
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    • v.7 no.4
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    • pp.419-430
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    • 2009
  • Reading comprehension (RC) systems are to understand a given text and return answers in response to questions about the text. Many previous studies extract sentences that are the most similar to questions as answers. However, texts for RC tests are generally short and facts about an event or entity are often expressed in multiple sentences. The answers for some questions might be indirectly presented in the sentences having few overlapping words with the questions. This paper proposes a conceptual graph matching method towards RC tests to extract answer strings. The method first represents the text and questions as conceptual graphs, and then extracts subgraphs for every candidate answer concept from the text graph. All candidate answer concepts will be scored and ranked according to the matching similarity between their sub-graphs and question graph. The top one will be returned as answer seed to form a concise answer string. Since the sub-graphs for candidate answer concepts are not restricted to only covering a single sentence, our approach improved the performance of answer extraction on the Remedia test data.

A Mapping Method of Data-flow graphs into Systolic Arrays (Data-flow graph 로부터 Systolic Array에의 변환방법)

  • Park, Myong-Soon;Jhon, C.S.
    • Proceedings of the KIEE Conference
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    • pp.1121-1124
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    • 1987
  • Previous methods to map from a FORTRAN-like specification into a systolic array were difficult to find data dependencies because the specification was expressed and executed sequentially. Data-flow graph(DFG)s show data dependencies explicitly. In this paper we show a mapping tool from a DFG specification into a systolic array. We introduce the concept of a Systolic Pattern Stream(SPS) and use that concept to derive a systolic array.

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