• Title/Summary/Keyword: 온톨로지 저장소

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지능형 전자상거래를 위한 온톨로지의 효율적인 생성

  • Kim, Tae-Seok;Yang, Jin-Hyeok;Lee, Ji-Hong;Son, Jong-Su;Jeong, In-Jeong
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2005.11a
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    • pp.273-279
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    • 2005
  • 월드와이드웹 (WWW) 기반의 전자상거래는 주로 데이터베이스를 기반으로 서비스를 제공하고 있다. 그러나 월드와이드웹 기반의 전자상거래는 단순 키워드 검색에만 의존하고 있다. 이러한 검색은 데이터베이스 자체로는 의미적인 정보를 효과적으로 처리하기에는 많은 문제점이 있다. 1999년 말에 의미적인 정보를 효과적으로 처리하기 할 수 있는 시맨틱 웹 이 제안되었다. 시맨틱 웹은 의미적인 정보를 담고 있는 지식베이스(Knowledge Bases)인 온톨로지를 기반으로 하고 있다. 그러나 온툴로지의 생성은 많은 부분을 휴리스틱에 의존하고 있기 때문에 많은 시간과 비용이 소비된다. 따라서 우리는 이와 같은 문제를 해결하기 위하여 데이터베이스에서 온톨로지를 생성하는 방법을 제안한다. 데이터베이스는 도메인을 잘 나타내고 있는 정보의 저장소이므로 데이터베이스로부터의 온톨로지 생성은 분석, 설계 등의 사전 작업이 필요하지 않아 시간과 비용의 소비를 줄 일 수 있는 장점이 있다. 우리는 데이터베이스에서 스키마를 추출, 뼈대그래프$^{1}$ 를 생성하고 개념그래프로 확장하여 도메인을 잘 나타낼 수 있는 온톨로지를 생성하는 알고리즘을 제안하고 제안된 알고리즘을 통하여 온톨로지를 생성을 함으로서 제안된 생성 방법을 검증한다. 제안한 방법으로 생성된 온톨로지는 단순 키워드 검색에서 의미적인 검색을 할 수 있는 시맨틱 웹 서비스의 기반이 되므로 의미적 검색이 가능한 전자상거래 서비스를 구축하는데 시간과 비용의 소비를 줄임으로 차세대 전자상거래의 초석이 된다.

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Knowledge Description Model For Multi-Agent Systems (다중 에이전트 시스템을 위한 지식 표현 모델)

  • Kim Hoon-Min;Jee Hyeng-Whan;Yang Jung-Jin
    • Proceedings of the Korean Information Science Society Conference
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    • 2006.06b
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    • pp.205-207
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    • 2006
  • 이질적이고 분산된 환경에서의 컴퓨팅 요소들은 변화하는 사용자의 요구와 상황을 인지하여 주위 환경에 적응할 필요가 있으며 이렇게 자동화된 요소, 즉 적응된 에이전트들은 동적으로 설정된 목표를 해결하기 위해 서로 협력해야 한다. 이렇게 적응된 에이전트를 구현하기 위해서는 이들이 인지된 상황을 추론할 수 있는 지식베이스의 구축이 필수적이며 이러한 지식을 표현할 수 있는 모델이 필요하다. 본고에서는 다중 에이전트 시스템에서 지적 활동의 중심적 자료구조가 될 온톨로지와 온톨로지를 효과적으로 관리하는 온톨로지 저장소를 활용하여 다양한 지식원과 에이전트간의 의미적 상호작용을 증대시키기 위한 Knowledge Description Model을 제시한다.

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On the Structure of a Knowledge-Based Mold Design System (지식 기반 사출 금형 설계시스템 구조)

  • Kang M.;Eum K.H.;Kim T.S.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.10a
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    • pp.119-123
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    • 2005
  • Mold design is a knowledge-intensive decision making process where product designer, injection molding engineer as well as mold designer affect each other. Representation and management of design knowledge is a prerequisite for an intelligent design system, which aims to guide and support designer to carry out design activity in more efficient way by avoiding or minimizing unnecessary trial and errors. This paper discusses the issues in knowledge-based mold design, and describes the structure of a knowledge-based mold design system fur parts with micro features under development.

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The study of Query Method for keyword disambiguation based on TMDR (TMDR 기반의 키워드 모호성 해결을 위한 질의 기법에 관한 연구)

  • Jung, Gye-Dong;Hwang, Chi-Gon;Shin, Hyo-young;Choi, Young-Gun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2010.04a
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    • pp.177-179
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    • 2010
  • 키워드의 모호성으로 인한 검색 결과가 부정확하게 되는 문제를 해결하기 위한 질의기법을 제안한다. 제안하는 질의 기법은 TMDR을 이용한다. TMDR은 로컬 데이터베이스를 통합하기 위한 스키마 정보의 통합 관리하기위한 MDR과 데이터 접근을 위해 온톨로지 지식 저장소로 토픽맵으로 구성된다. 토픽맵은 연관관계 분석을 통한 데이터 모호성 해결을 지원한다. 이를 이용하여 기존 시스템의 이질적 문제를 해결한다. 토픽맵은 지식을 제공하고, 지식 간의 관계성을 제공하므로 키워드의 모호성을 해결할 수 있다. 본 논문에서는 이러한 TMDR을 이용하여 키워드의 모호성과 기존 시스템의 이질적 환경을 적응하기 위한 질의기법을 제안한다.

A New Keyword Search Algorithm for RDF/S and OWL Documents (RDF/S 및 OWL 문서에 대한 키워드 검색 알고리즘)

  • Kim, Hak Soo;Son, Jin Hyun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2009.04a
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    • pp.321-324
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    • 2009
  • XML 또는 RDBMS 에서의 키워드 검색은 기존의 정보 검색처럼 데이터의 구조 또는 질의 언어에 대한 사전 지식 없이 질의 처리를 수행하는 연구 분야 중의 하나이다. 오늘날 키워드 검색을 효율적으로 처리하기 위해 제안된 연구들은 그래프 기반의 질의 처리에 기반한 기법들에 초점을 두고 있다. 이러한 접근들은 XML 또는 RDBMS 안에 존재하는 데이터를 그래프 구조에 기반한 데이터로 변환한 다음에 그래프 탐색을 통해서 모든 질의 키워드를 포함하는 결과들을 찾는다. 그러나 기존의 기법들을 RDF/S 또는 OWL 문서와 같은 복잡한 그래프 구조에 적용하기에는 질의 성능 측면에서 많은 문제점을 가지고 있다. 또한, 온톨로지 언어의 의미적 단위로서의 RDF 트리플을 고려하지 않기 때문에 질의 결과에 대한 신뢰성을 보장할 수 없다. 이러한 관점에서 본 논문은 RDF/S 또는 OWL 저장소에서 효율적이고 의미적인 키워드 검색을 위한 인덱싱 기법 및 알고리즘을 설계한다.

PSR: Pre-Computing Solutions in RDBMS for Efficient Web Services Composition Search (PSR : 효율적인 웹 서비스 컴포지션 검색을 위한 RDBMS 기반의 선 계산 기법)

  • Kwon, Joon-Ho;Park, Kyu-Ho;Lee, Dae-Wook;Lee, Suk-Ho
    • Journal of KIISE:Databases
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    • v.35 no.4
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    • pp.333-344
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    • 2008
  • In recent years, the web services composition has received much attention. By web services composition, we mean providing a new service that does not exist on the repository. In this paper, we propose a new system called PSR for web services composition search using a relational database. We also propose algorithms for pre-computing web services composition using joins and indices. We store ontologies from web services in RDBMS, so that the PSR system returns web services composition in order of similarity with user query through the degree of the ontology matching. We demonstrated that our pre-computing web services composition approach in RDBMS yields lower execution time and good scalability when handling a large number of web services and user queries.

Ontology-based Course Mentoring System (온톨로지 기반의 수강지도 시스템)

  • Oh, Kyeong-Jin;Yoon, Ui-Nyoung;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.149-162
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    • 2014
  • Course guidance is a mentoring process which is performed before students register for coming classes. The course guidance plays a very important role to students in checking degree audits of students and mentoring classes which will be taken in coming semester. Also, it is intimately involved with a graduation assessment or a completion of ABEEK certification. Currently, course guidance is manually performed by some advisers at most of universities in Korea because they have no electronic systems for the course guidance. By the lack of the systems, the advisers should analyze each degree audit of students and curriculum information of their own departments. This process often causes the human error during the course guidance process due to the complexity of the process. The electronic system thus is essential to avoid the human error for the course guidance. If the relation data model-based system is applied to the mentoring process, then the problems in manual way can be solved. However, the relational data model-based systems have some limitations. Curriculums of a department and certification systems can be changed depending on a new policy of a university or surrounding environments. If the curriculums and the systems are changed, a scheme of the existing system should be changed in accordance with the variations. It is also not sufficient to provide semantic search due to the difficulty of extracting semantic relationships between subjects. In this paper, we model a course mentoring ontology based on the analysis of a curriculum of computer science department, a structure of degree audit, and ABEEK certification. Ontology-based course guidance system is also proposed to overcome the limitation of the existing methods and to provide the effectiveness of course mentoring process for both of advisors and students. In the proposed system, all data of the system consists of ontology instances. To create ontology instances, ontology population module is developed by using JENA framework which is for building semantic web and linked data applications. In the ontology population module, the mapping rules to connect parts of degree audit to certain parts of course mentoring ontology are designed. All ontology instances are generated based on degree audits of students who participate in course mentoring test. The generated instances are saved to JENA TDB as a triple repository after an inference process using JENA inference engine. A user interface for course guidance is implemented by using Java and JENA framework. Once a advisor or a student input student's information such as student name and student number at an information request form in user interface, the proposed system provides mentoring results based on a degree audit of current student and rules to check scores for each part of a curriculum such as special cultural subject, major subject, and MSC subject containing math and basic science. Recall and precision are used to evaluate the performance of the proposed system. The recall is used to check that the proposed system retrieves all relevant subjects. The precision is used to check whether the retrieved subjects are relevant to the mentoring results. An officer of computer science department attends the verification on the results derived from the proposed system. Experimental results using real data of the participating students show that the proposed course guidance system based on course mentoring ontology provides correct course mentoring results to students at all times. Advisors can also reduce their time cost to analyze a degree audit of corresponding student and to calculate each score for the each part. As a result, the proposed system based on ontology techniques solves the difficulty of mentoring methods in manual way and the proposed system derive correct mentoring results as human conduct.

OWL/Relational Mapping Rules to Use Relational Databases as OWL 2 Web Ontologies (관계형 데이터베이스를 OWL 2 웹 온톨로지로 사용하기 위한 OWL/관계형 매핑 규칙)

  • Choi, Ji-Woong;Kim, Myung-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.7
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    • pp.35-47
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    • 2011
  • This paper proposes a set of rules to automatically generate OWL ontologies from relational databases. The purpose of the rules is to allow semantic access to existing RDB data without any database schema transformation and data migration process. In other words, the rules help a RDBMS play as a web ontology repository as well. However, the use of the mapping rules between RDB and OWL proposed by other studies for the objective causes troubles as follows. First, databases including the tables with a specific structure can't be translated into OWL. Second, the process for extracting an OWL individual unnecessarily lead to database join operations, or several SQL queries. On the other hand, our rules is designed to prevent these problems, can generate OWL classes and properties from database schemas and can generate OWL individuals from the database instances. In addition, an ontology generated by our rules is an OWL 2 DL ontology.

The Design of XMDR Data Hub for Efficient Business Process Operation (효율적인 비즈니스 프로세스 운용을 위한 XMDR 데이터 허브 설계)

  • Hwang, Chi-Gon;Jung, Gye-Dong;Choi, Young-Keun
    • The KIPS Transactions:PartD
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    • v.18D no.3
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    • pp.149-156
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    • 2011
  • Recently, enterprise systems require the necessity of integration for data sharing and cooperation. As a methodology for integration, Service-Oriented Architecture for service integration and Master Data for integration of data, which is used for service, were appeared. This paper suggests a method that operates BP(Business Process) efficiently. We make XMDR(eXtended Meta Data Registry) as knowledge-repository to support the BP and construct data hubs to operate it. XMDR manages MDM(Master Data Management) to integrate the data, resolves heterogeneity between the data and provides relationship to the business efficiently. This is composed of MDR(Meta Data Registry), ontology and BR(Business Relations). MDR describes relationship between meta data to solve structured heterogeneity. Ontology describes semantic heterogeneity and relationship between data. BR describes relationship between tasks. XMDR data hub supports the management of master data and interaction of different process effectively.

A Query Processing Method for Hierarchical Structured e-Learning System (계층적으로 구조화된 이러닝 시스템을 위한 질의 처리 기법)

  • Kim, Youn-Hee;Kim, Jee-Hyun
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.3
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    • pp.189-201
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    • 2011
  • In this paper, we design an ontology which provides interoperability by integrating typical metadata specifications and defines concepts and semantic relations between concepts that are used to describe metadata for learning objects in university courses. And we organize a hierarchical structured e-Learning system for efficient retrieval of learning objects on many local storages that use different specifications to describe metadata and propose a query processing method based on inferences. The proposed e-Learning system can provide more accurate and satisfactory retrieval service by using the designed ontology because both learning objects that be directly connected to user queries and deduced learning objects that be semantically connected to them are retrieved.