• Title/Summary/Keyword: 온톨로지 추출

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Semi-Automatic Ontology Generation about XML Documents using Data Mining Method (데이터 마이닝 기법을 이용한 XML 문서의 온톨로지 반자동 생성)

  • Gu Mi-Sug;Hwang Jeong-Hee;Ryu Keun-Ho;Hong Jang-Eui
    • The KIPS Transactions:PartD
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    • v.13D no.3 s.106
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    • pp.299-308
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    • 2006
  • As recently XML is becoming the standard of exchanging web documents and public documentations, XML data are increasing in many areas. To retrieve the information about XML documents efficiently, the semantic web based on the ontology is appearing. The existing ontology has been constructed manually and it was time and cost consuming. Therefore in this paper, we propose the semi-automatic ontology generation technique using the data mining technique, the association rules. The proposed method solves what type and how many conceptual relationships and determines the ontology domain level for the automatic ontology generation, using the data mining algorithm. Appying the association rules to the XML documents, we intend to find out the conceptual relationships to construct the ontology, finding the frequent patterns of XML tags in the XML documents. Using the conceptual ontology domain level extracted from the data mining, we implemented the semantic web based on the ontology by XML Topic Maps (XTM) and the topic map engine, TM4J.

Incremental Enrichment of Ontologies through Feature-based Pattern Variations (자질별 관계 패턴의 다변화를 통한 온톨로지 확장)

  • Lee, Sheen-Mok;Chang, Du-Seong;Shin, Ji-Ae
    • The KIPS Transactions:PartB
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    • v.15B no.4
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    • pp.365-374
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    • 2008
  • In this paper, we propose a model to enrich an ontology by incrementally extending the relations through variations of patterns. In order to generalize initial patterns, combinations of features are considered as candidate patterns. The candidate patterns are used to extract relations from Wikipedia, which are sorted out according to reliability based on corpus frequency. Selected patterns then are used to extract relations, while extracted relations are again used to extend the patterns of the relation. Through making variations of patterns in incremental enrichment process, the range of pattern selection is broaden and refined, which can increase coverage and accuracy of relations extracted. In the experiments with single-feature based pattern models, we observe that the features of lexical, headword, and hypernym provide reliable information, while POS and syntactic features provide general information that is useful for enrichment of relations. Based on observations on the feature types that are appropriate for each syntactic unit type, we propose a pattern model based on the composition of features as our ongoing work.

On developing OWL Analyzer based on Formal Concept Analysis (형식개념분석기법 기반의 온톨로지 분석도구(OWL Analyzer)의 개발)

  • Kim, Dong-Soon;Hwang, Suk-Hyung;Kim, Hong-Gee;Yang, Kyung-Mo
    • Proceedings of the Korea Information Processing Society Conference
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    • 2006.11a
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    • pp.7-10
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    • 2006
  • 온톨로지는 시멘틱 웹의 상호운용성에 있어서 가장 중요한 역할을 하고 있으며, 다양한 분야에서 지식의 공유 및 재사용을 목적으로 사용되고 있다. 현재 대부분의 온톨로지들은 도메인 전문가나 온톨로지 개발자들이 $Prot\acute{e}g\acute{e}$와 같은 도구를 사용하여 수작업으로 구축되어 지고 있다. 비록 전문가들이 $Prot\acute{e}g\acute{e}$와 같은 도구를 사용할지라도, OWL등과 같은 언어로 구축된 온톨로지가 실용적이고 도메인의 정보를 정확하게 반영하였음을 검증하는 것은 쉽지 않다. 따라서 본 연구에서는 형식개념분석기법(Formal Concept Analysis)을 사용하여, OWL로 구축된 온톨로지의 소스로부터 온톨로지의 주요 요소들을 추출, 분석하여 구조적 문제점을 파악 할 수 있는 OWL온톨로지 분석도구(OWL Analyzer)의 개발에 대하여 설명한다. 본 연구에서 개발된 OWL Analyzer를 사용함으로써, 구축된 온톨로지내에 포함된 오류를 수월하게 파악할 수 있고, 온톨로지 개발자에게 보다 좋은 개념계층구조를 갖는 온톨로지를 제안할 수 있다.

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An Extraction of Property of Ontology Instance Using Stratification of Domain Knowledge (도메인지식의 계층화를 통한 온톨로지 인스턴스의 속성정보 추출)

  • Chang, Moon-Soo;Kang, Sun-Mee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.3
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    • pp.291-296
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    • 2007
  • The ontology has been used widely in recent years with its aim to accumulate knowledge that machine can comprehend. We believe that machine can manage and analyze information on its own using the ontology. In this paper, we propose an algorithm that allows us to extract properties of ontology instances from structured information already existing in web documents. In particular, by stratification of the domain knowledge that is composed of property information, we were able to make the algorithm better and improve the quality of extraction results. In our experiments with 20 thousands targeted documents, we were able to extract property information with 83% confidence.

Construction of Construction Drawing Data Repository using Ontology (온톨로지를 이용한 건축 도면데이터 레포지터리 구성)

  • Lee, Hui-Jae;Yoo, Sang-Bong;Kim, In-Han
    • The Journal of Society for e-Business Studies
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    • v.9 no.3
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    • pp.79-94
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    • 2004
  • W3C has developed the RDF standard for utilizing ontology in Web applications. This paper presents extracting, storing, and applying ontology on product data. The management and document information included in DWG files is focused as an example. By analyzing the relationship among the drawing data, the RDF schema is designed frist. Based on the schema ontology is extracted and stored in XML files. As an application of the stored ontology, we the schema ontology is extracted and stored in XML files. As an application of the stored ontology, we can reconfigure the sitemap of drawing data repositories. In this example, the users can select the view that he or she is interested in (e.g., designer, document, project). With such various views of an drawing data repository, the users can access the specific data more effectively.

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Verb Clustering for Defining Relations between Ontology Classes of Technical Terms Using EM Algorithm (EM 알고리즘을 이용한 전문용어 온톨로지 클래스간 관계 정의를 위한 동사 클러스터링)

  • Jin, Meixun;Nam, Sang-Hyob;Lee, Yong-Hoon;Lee, Jong-Hyeok
    • Annual Conference on Human and Language Technology
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    • 2007.10a
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    • pp.233-240
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    • 2007
  • 온톨로지 구축에서 클래스간 관계 설정은 중요한 부분이다. 본 논문에서는 클래스간 상 하위 관계 외의 관계 설정을 위한 클래스간 관계 자동 정의를 목적으로 의존구문분석의 (주어, 용언) (목적어, 용언) 쌍들을 추출하고, 이렇게 추출된 데이터를 이용하여 용언들을 클러스터링 하는 방법을 제안한다. 도메인 전문 코퍼스 데이터 희귀성 문제를 해결하고자, 웹검색을 결합한 방식을 선택하여 도메인 온톨로지 구축 클래스간 관계 자동 설정에 대한 방법론을 제시한다.

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Semantic Ontology Speech Recognition Performance Improvement using ERB Filter (ERB 필터를 이용한 시맨틱 온톨로지 음성 인식 성능 향상)

  • Lee, Jong-Sub
    • Journal of Digital Convergence
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    • v.12 no.10
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    • pp.265-270
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    • 2014
  • Existing speech recognition algorithm have a problem with not distinguish the order of vocabulary, and the voice detection is not the accurate of noise in accordance with recognized environmental changes, and retrieval system, mismatches to user's request are problems because of the various meanings of keywords. In this article, we proposed to event based semantic ontology inference model, and proposed system have a model to extract the speech recognition feature extract using ERB filter. The proposed model was used to evaluate the performance of the train station, train noise. Noise environment of the SNR-10dB, -5dB in the signal was performed to remove the noise. Distortion measure results confirmed the improved performance of 2.17dB, 1.31dB.

Semantic Ontology Speech Information Extraction using Non-parametric Correlation Coefficient (비모수적 상관계수를 이용한 시맨틱 온톨로지 음성 정보 추출)

  • Lee, Byungwook
    • Journal of Digital Convergence
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    • v.11 no.9
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    • pp.147-151
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    • 2013
  • On retrieving high frequency keywords in information retrieval system, mismatchings to user's request are problems because of the various meanings of keywords in the existing ontology configuration. In this paper, it is to construct personnel selection ontology and rules in personnel management which are composed of various concepts and knowledges based on semantic web technology and suggest selection procedures to support these rules and knowledge retrieval system to verify suitability of selection results. This system utilizes a method of extraction of speech features by using non-parametric correlation coefficient. This proposed method has been validated by showing that the result average SNR of the experiment evaluation of the proposed techniques was shown to be decreased by .752dB.

Extracting keyword of emerging technology using ontology learning in cool vendor (온톨로지 학습을 이용한 쿨벤더의 미래유망기술 키워드 추출)

  • Lee, tae-kyun;Sin, gun-chul;Kim, su-kyeong
    • Proceedings of the Korea Contents Association Conference
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    • 2016.05a
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    • pp.75-76
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    • 2016
  • 최근 많은 기업 중에서 가트너는 매년 미래유망기술과 쿨벤더를 발표한다. 우리는 쿨벤더에서 제공하는 여러 정보들을 분석하여 미래유망기술에 대한 키워드를 찾고 이것을 실제 기술명과 연관짓고자 한다. 이 모든 과정의 전체적인 그림이 온톨로지 모델에 담긴다. 이 연구는 향후 어떤 집단의 미래를 이끌어갈 핵심 기술을 찾고자 하는 결정권자들에게 도움이 될 것이다.

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OWL 온톨로지 파서와 추론 시스템 설계 및 구현

  • Hwang, Myeong-Gwon;Gong, Hyeon-Jang;Kim, Pan-Gu
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2005.11a
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    • pp.290-294
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    • 2005
  • 의미적인 정보검색을 위한 시맨틱 웹에 대한 연구가 본격화되었다. 시맨틱 웹을 위한 핵심은 개념과 개념들 사이의 관계를 정의한 온톨로지이다. 온톨로지를 분석하고, 분석된 결과에 포함되어 있는 새로운 사실들을 추론하여 가능한 많은 결과를 이끌어 내는 것이 의미적인 정보검색의 기반이라 할 수 있다. 본 논문은 이러한 온톨로지에 정의된 개념들을 분석하는 범용적이고 빠른 파서와 파서를 통해 분석된 사실을 바탕으로 더욱 많은 새로운 사실을 추출할 수 있는 온톨로지 기반의 추론(Inference) 시스템을 설계하고 구현하였다.

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