• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.471-472
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• 2006

• Journal of the Korean Society for information Management
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• v.6 no.2
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• pp.87-103
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• 1989

In this study, A DDC online system was developed which provides subject access and browsing function for class numbers or subject terms. A knowledgebase of the DDC Schedules and Relative Index was designed for this purpose using IBM-PC. From the DDC 20th edition, subjects from 004 to 006, covering‘data processing’,‘computer science’‘programming and progrms’, and etc., were selected for this experiment. DDC schedules are represented as a frame structure which is apt to describe hierachical structures. This experiment, joining the DDC to the information retrieval environment of an online catalog, will contribute to the future of the online DDC system by providing possiblities for search strategies not feasible through the alphabetical approach of subject headings and keywords presently supported by online catalogs.

• Korean Journal of Computational Design and Engineering
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• v.21 no.2
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• pp.99-110
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• 2016

The quality of building space program is a key to measure how the building performance satisfies its owner and users. However assuring its efficiency requires reliable criteria that reflect high level experience knowledge in the field. This study suggests a plan to gauge the level of building space performance using expert knowledge, which has not been utilized well enough but should play a critical role. In order to setup an expert system measuring level of the space program, we firstly optimized the space areas to the best case in a knowledgebase and use them as criteria to judge the quality of the spaces extracted from BIM model. We found the experimental results show us a promising way of measuring a relative quality of the space programs.

• Journal of the Korean Society for information Management
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• v.5 no.1
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• pp.131-152
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• 1988

It is purposed in this paper to improve the retrieval cffect~venebs through the use of the seman-- t r knowledge of search terms in a computerbased search system. This study is developed it1 three stages include the experimentation of index terms or1 the probab~listir model, indexing with relational operators, and knowledgebase design. The sl~bject experimerltrd is the specific fklds of Chemical Engineering, ' Fluid Flow' and 'Combustion: As for the system ~rnplementatlon. two kinds of search method a r e done. Orie is to search terms related to one specialty word, the other is to retriele the articles based or1 the gueries.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.484-486
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• 2005

본 논문은 백과사전 도메인의 지식베이스 설계 및 통계기반 정보추출 방법을 이용한 속성정보 인식에 대하여 기술한다. 층 13개 카테고리로 구성된 백과사전에 대해 99개의 템플릿과 285개의 속성을 정의하였으며, 각 표제어의 추출 대상인 속성정보는 표제어를 설명하는 본문에서 통계기반 기계학습모델인 CRF(Conditional Random Fields)를 적용하여 추출하였다. 백과사전 카테고리 별로 균일하게 선정된 4천 5백 문서를 학습에 사용하였고 테스트 문서셋 500문서에 대해 속성인식률을 측정하였다. 성능 평가한 결과, $F1\;55.76\%\;(P\;74.89\%,\;R\;44.42\%)$의 성능을 나타내었다.

• The KIPS Transactions:PartD
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• v.14D no.2
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• pp.203-210
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• 2007

Ontology can be used as a formal and demonstrative knowledgebase that can express the thinking process of human. Software Development Process is a collection of ideal practices and procedural system that is performed by mature organization with high capability. Due to complexity of process, however, Software development Process often results in obstruction of introducing and improving simple process activity. While introducing and improving software development process, application of ontology to complex software development process is more approachable by showing deductive results of relationship between ISO/IEC 15504 and CMMI. In this paper, we demonstrate a methodology that utilizes the improved process database conceptually mapping between ISO/IEC 15504 and CMMI using ontology.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.