• 제목/요약/키워드: Conceptual Graph

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INFORMATION SEARCH BASED ON CONCEPT GRAPH IN WEB

  • Lee, Mal-Rey;Kim, Sang-Geun
    • Journal of applied mathematics & informatics
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    • 제10권1_2호
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    • pp.333-351
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    • 2002
  • This paper introduces a search method based on conceptual graph. A hyperlink information is essential to construct conceptual graph in web. The information is very useful as it provides summary and further linkage to construct conceptual graph that has been provided by human. It also has a property which shows review, relation, hierarchy, generality, and visibility. Using this property, we extracted the keywords of web documents and made up of the conceptual graph among the keywords sampled from web pages. This paper extracts the keywords of web pages using anchor text one out of hyperlink information and makes hyperlink of web pages abstract as the link relation between keywords of each web page. 1 suggest this useful search method providing querying word extension or domain knowledge by conceptual graph of keywords. Domain knowledge was conceptualized knowledged as the conceptual graph. Then it is not listing web documents which is the defect of previous search system. And it gives the index of concept associating with querying word.

개념그래프 도구의 기능 및 특성 조사 (A Survey on Functions and Characteristics of Conceptual Graph Tools)

  • 양기철
    • 디지털융복합연구
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    • 제12권12호
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    • pp.285-292
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    • 2014
  • 지능형 시스템은 자료나 정보보다 지식을 주로 이용하는 시스템이다. 따라서 지식표현은 지능형 시스템 구축에 있어서 중요한 요소이다. 개념그래프는 지식을 효율적으로 표현할 수 있는 그래프 형태의 논리적 지식표현 언어이다. 하지만 개념그래프를 직접 프로그래밍에 활용하기는 쉽지 않다. 이러한 어려움을 극복하기 위하여 여러 가지 도구들이 개발되었다. 본 논문에서는 개념그래프를 이용한 지능형 시스템 구축에 활용할 수 있는 도구들에는 어떤 것들이 있는지 조사하고 그들의 기능과 특성을 비교 분석한다. 조사결과는 지능형 시스템 구축을 위한 개념그래프 활용에 큰 도움이 될 것이다.

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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    • 제7권4호
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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.

Knowledge Conversion between Conceptual Graph Model and Resource Description Framework

  • 김진성
    • 한국지능시스템학회논문지
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    • 제17권1호
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    • pp.123-129
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    • 2007
  • On the Semantic Web, the content of the documents must be explicitly represented through metadata in order to enable contents-based inference. In this study, we propose a mechanism to convert the Conceptual Graph (CG) into Resource Description Framework (RDF). Quite a large number or representation languages for representing knowledge on the Web have been established over the last decade. Most of these researches are focused on design of independent knowledge description. On the Semantic Web, however, a knowledge conversion mechanism will be needed to exchange the knowledge used in independent devices. In this study, the CG could give an entire conceptual view of knowledge and RDF can represent that knowledge on the Semantic Web. Then the CG-based object oriented PROLOG could support the natural inference based on that knowledge. Therefore, our proposed knowledge conversion mechanism will be used in the designing of Semantic Web-based knowledge representation and inference systems.

PROLOG와 개념 그래프를 이용한 협동 온톨로지의 설계 (Design of Cooperation Ontology by using PROLOG and Conceptual Graph)

  • 김진성
    • 한국지능시스템학회:학술대회논문집
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    • 한국퍼지및지능시스템학회 2006년도 추계학술대회 학술발표 논문집 제16권 제2호
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    • pp.314-317
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    • 2006
  • This study proposes an ontology design framework to support the cooperation among devices by using PROLOG, Conceptual Graph (CG), and Resource Description Framework (RDF). Quite a large number of representation languages for representing ontology on the Web have been established over the last decade. Most of these researches are focused on design of independent resources description. In Semantic Web, however, cooperation ontology will be needed. In this study, the CG could make an entire conceptual view of knowledge and RDF can represent that knowledge. Then the PROLOG could support the natural inference based on that knowledge. Therefore, our proposed ontology will be used in the designing of Semantic Web-based cooperation systems.

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개념 그래프 기반의 효율적인 악성 코드 탐지 기법 (A Method for Efficient Malicious Code Detection based on the Conceptual Graphs)

  • 김성석;최준호;배용근;김판구
    • 정보처리학회논문지C
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    • 제13C권1호
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    • pp.45-54
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    • 2006
  • 현재까지 존재하는 무수한 악성 행위에 대응하기 위해서 다양한 기법들이 제안되었다 그러나 현존하는 악성행위 탐지 기법들은 기존의 행위에 대한 변종들과 새로운 형태의 악성행위에 대해서 적시 적절하게 대응하지 못하였고 긍정 오류(false positive)와 틀린 부정(negative false) 등을 해결하지 못한 한계점을 가지고 있다. 위와 같은 문제점을 개선하고자 한다. 여기서는 소스코드의 기본 단위(token)들을 개념화하여 악성행위 탐지에 응용하고자 한다. 악성 코드를 개념 그래프로 정의할 수 있고, 정의된 그래프를 통하여 정규화 표현으로 바꿔서 코드 내 악성행위 유사관계를 비교할 수 있다. 따라서 본 논문에서는, 소스코드를 개념 그래프화하는 방법을 제시하며, 정확한 악성행위 판별을 위한 유사도 측정방안을 제시한다. 실험결과, 향상된 악성 코드 탐지율을 얻었다.

효율적인 개념 클러스터링 기법 (An Efficient Conceptual Clustering Scheme)

  • 양기철
    • 한국엔터테인먼트산업학회논문지
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    • 제14권4호
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    • pp.349-354
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    • 2020
  • 본 논문에서는 개체를 자유롭게 설명하고 효율적으로 클러스터링을 수행 할 수 있는 개념 그래프 기반의 새로운 클러스터링 체계 Clustering scheme Based on Conceptual graphs(CBC)를 제안한다. 개념적 클러스터링은 기계 학습 기술 중 하나이다. 개념 클러스터링에서 개체 간의 유사성은 개체의 의미나 환경을 고려하지 않고 유사성을 결정하는 일반적인 클러스터링 체계와 달리 개념 구성원의 자격에 따라 결정된다. 이 논문에서는 다양한 개체를 개념 그래프로 자유롭게 설명하여 효율적인 개념 클러스터링을 수행 할 수 있는 새로운 개념 클러스터링 체계인 CBC를 소개한다.

그래프 기반 한의 예후 분석 - 팔강육음, 기혈진액, 장부 변증을 중심으로 - (Analysis of Prognosis Graphs in Korean Medicine)

  • 김상균;김안나
    • 동의생리병리학회지
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    • 제26권6호
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    • pp.818-822
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    • 2012
  • We in this paper propose a prognosis graph, analyzing prognoses of each pattern described in the Korean medicine literatures. This graph is represented as the integrated graphs about knowledge of patterns and their transitions in the prognoses, where a node becomes a pattern name and a edge becomes a transition between patterns, along with a condition with respect to cause or mechanism of the pattern. The knowledge of prognoses which a pattern is transit into another pattern can be identified at a glance by using this model. We also construct a upper-level prognosis graph, excluding five viscera and six entrails from the model. This upper-level prognosis graph contains the conceptual knowledge than clinical one so that it may be helpful to students and researchers in the Korean medicine fields.

Automatic Extraction of Metadata Information for Library Collections

  • Yang, Gi-Chul;Park, Jeong-Ran
    • International Journal of Advanced Culture Technology
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    • 제6권2호
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    • pp.117-122
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    • 2018
  • As evidenced through rapidly growing digital repositories and web resources, automatic metadata generation is becoming ever more critical, especially considering the costly and complex operation of manual metadata creation. Also, automatic metadata generation is apt to consistent metadata application. In this sense, metadata quality and interoperability can be enhanced by utilizing a mechanism for automatic metadata generation. In this article, a mechanism of automatic metadata extraction called ExMETA is introduced in order to alleviate issues dealing with inconsistent metadata application and semantic interoperability across ever-growing digital collections. Conceptual graph, one of formal languages that represent the meanings of natural language sentences, is utilized for ExMETA as a mediation mechanism that enhances the metadata quality by disambiguating semantic ambiguities caused by isolation of a metadata element and its corresponding definition from the relevant context. Hence, automatic metadata generation by using ExMETA can be a good way of enhancing metadata quality and semantic interoperability.

Handling Semantic Ambiguity for Metadata Generation

  • Yang, Gi-Chul;Park, Jeong-Ran
    • International Journal of Internet, Broadcasting and Communication
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    • 제10권2호
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    • pp.1-6
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    • 2018
  • The following research questions are examined in this paper. What hinders quality metadata generation and metadata interoperability? What kind of semantic representation technique can be utilized in order to enhance metadata quality and semantic interoperability? This paper suggests a way of handling semantic ambiguity for metadata generation. The conceptual graph is utilized to disambiguate semantic ambiguities caused by isolation of a metadata element and its corresponding definition from the relevant context. The mechanism introduced in this paper has the potential to alleviate issues dealing with inconsistent metadata application and interoperability across digital collections.