• 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.

• IE interfaces
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• v.23 no.3
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• pp.213-220
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• 2010

As the market becomes increasingly globalized and competition among companies increases in severity, various specialized organizations are participating across the process plant lifecycle, including the stages of design, construction, operation and maintenance, and dismantlement, in order to ensure efficiency and elevate competitiveness. In this regard, it is an important technical issue to develop services or information systems for sharing process plant data among participating organizations. ISO 15926 is an international standard for integration of lifecycle data for process plants including oil and gas facilities. ISO 15926 Part 7, a part of the ISO 15926 standard, specifies an implementation method called a facade that uses Web Services and ontology technologies for constructing plant data repositories and related services, with the aim of sharing lifecycle data of process plants. This paper discusses the ISO 15926-based prototype facade implemented for storing equipment data of nuclear power plants and servicing the data to interested organizations.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.311-320
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• 2002

시맨틱 웹은 인간이 이해하는 것처럼 웹 문서의 의미를 컴퓨터가 처리할 수 있도록 하는데 있다. 그러나 인터넷 등 정보통신 기술의 발전으로 인해 정보량이 급증함으로써 이들 정보 자원을 효과적으로 검색하기에는 많은 어려움이 있다. 이러한 문제점을 해결하기 위해 본 논문에서는 주석 에디터를 사용하여 논문에 대한 RDF 메타데이타의 자동 생성 방법을 제안한다. 사용자가 논문을 주석 처리할 때, 문서에 대한 특징을 추출하고 온토로지 인터페이스를 사용하여 문서를 분류한다. 구현된 시스템을 통해 사용자는 추출된 메타데이타를 메타데이타 뷰를 통해 볼 수 있으며, HTML 뷰를 통해 메타데이타를 수동으로 수정이 가능하다. 이 메타데이타는 RDF Repository로 저장할 수 있으며, 주석 뷰를 통하여 RDF 메타데이타 생성을 확인할 수 있다. 이렇게 생성된 RDF 메타데이타는 웹 로봇이 내용의 의미 파악 및 카테고리 정보를 쉽게 알 수 있도록 해준다. 본 논문은 검색 엔진을 통하여 논문 검색시 전체 내용보다 RDF 메타데이타 정보만으로 효율적인 검색을 할 수 있는 방법에 초점을 둔다.

• 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.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.4
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• pp.111-134
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• 2021

Recently, the preparation and submission of DMP is gradually becoming compulsory, centering on domestic government-funded research institutes. However, as DMP preparation is described in written or free text, there is a problem that research data management cannot be properly explained due to non-standardization and insufficient preparation in terms of standards, formats, and management. Therefore, in this study, a case study was conducted on a machine-readable DMP that can be automatically generated and maintained by a machine, and a method for applying maDMP was proposed. Examples of maDMP investigated included RDCS, Argos, Haplo Repository, and DMap. In addition, the use of permanent identifiers, application of controlled vocabulary, and application of semantic technologies such as ontology can be mentioned as possible ways to apply maDMP.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.6
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• pp.37-45
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• 2013

In this paper proposes the latest network-assisted online telemedicine service to coincide with the point being discussed for health care providers to match patients, patients with personalized medical service support system. In order to design the system, to understand the requirements of the patient personalized medical support service system, the data were normalized and were designed architecture client server structure. Further, in order to implement the system that was designed to define the structure of server and client, ontology repository, we implement the system. In this paper, as a result of the test by creating a scenario and prerequisites for testing patient personalized medical service support system that is design and implementation, selecting a patient's condition, department of symptoms by the selected but it was confirmed that the inference is, inference medical institutions that fits department inferred one following upon the items medical patient has the required.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.533-540
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• 2006

The semantic web environment promise semantic search of heterogeneous data from distributed web page. Semantic search would resuit in an overwhelming number of results for users is increased, therefore elevating the need for appropriate personalized ranking schemes. Culture Finder helps semantic web agents obtain personalized culture information. It extracts meta data for each web page(culture news, culture performance, culture exhibition), perform semantic search and compute result ranking point to base user profile. In order to work efficient, Culture Finder uses five major technique: Machine learning technique for generating user profile from user search behavior and meta data repository, an efficient semantic search system for semantic web agent, query analysis for representing query and query result, personalized ranking method to provide suitable search result to user, upper ontology for generating meta data. In this paper, we also present the structure used in the Culture Finder to support personalized search service.

• The KIPS Transactions:PartC
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• v.13C no.1 s.104
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• pp.129-136
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• 2006

Information Retrieval System aims towards providing fast and accurate information to users. However, current search systems are based on plain svntactic analysis which makes it difficult for the user to find the exact required information. This paper proposes the SW-IRS (Semantic Web-based Information Retrieval System) using an Ontology Server. The proposed system is purposed to maximize efficiency and accuracy of information retrieval of unstructured and semi-structured documents by using an agent-based automatic classification technology and semantic web based information retrieval methods. For interoperability and easy integration, RDF based repository system is supported, and the newly developed ranking algorithm was applied to rank search results and provide more accurate and reliable information. Finally, a new ranking algorithm is suggested to be used to evaluate performance and verify the efficiency and accuracy of the proposed retrieval system.

• Journal of KIISE:Software and Applications
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• v.34 no.8
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• pp.731-742
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• 2007

Self-growing software is a software system that has the capability of evolving its functionalities and configurations by itself based on dynamically monitored situations. Self-growing software is especially necessary for intelligent service robots, which must have the capability to monitor their surrounding environments and provide appropriate behaviors for human users. However, it is hard to anticipate all situations that robots face with, and it is hard to make robots have all functionalities for various environments. In addition, robots have limited internal capacity. To support self-growing software for intelligent service robots, we are developing a cell-based distributed repository system that allows robots and developers transparently to share robot functionalities. To accomplish the creation of evolutionary repositories, we invented the concept of a cell, which is a logical group of distributed repositories based upon the functionalities of components. In addition, a cell can be used as a unit for the evolutionary growth of the components within the repositories. In this paper, we describe the requirements and architecture of the cell-based repository system for self-growing software. We also present a prototype implementation and experiment of the repository system. Through the cell-based repositories, we achieve improved performance of self-growing actions for robots and efficient sharing of components among robots and developers.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.29-45
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• 2015

This paper proposes an implementation of SPARQL-DL, which is a query language for OWL ontologies, for query-answering over the OWL ontologies virtually generated from existing RDBs. The proposed SPARQL-DL processor internally translates input SPARQL-DL queries into SQL queries and then executes the translated queries. There are two advantages in the query processing method. First, another repository to store OWL ontologies generated from RDBs is not required. Second, a large ABox generated from an RDB instance is able to be served without using Tableau algorithm based reasoners which have a problem in large ABox reasoning. Our algorithm for query rewriting is designed to create one corresponding SQL query from one input SPARQL-DL query to minimize the overhead by establishing connections with RDBs.