• 디지털융복합연구
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• 제3권1호
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• pp.183-194
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• 2005

This study is aimed at building up an Ontology to solve the discrepancy of terminologies between teachers and students by showing, through Ontology, the knowledge for diagnosis of underachieving students. Also this study makes it possible to infer the diagnosis based on information of these underachieving students. In addition, while a general Underachieving Students diagnosis system shows special diagnosis, this Ontology system helps users obtain correct concepts through this knowledge based system, and suggest building an Ontology to extend unclear conceptual knowledge to clearer ones.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2007년도 춘계학술대회 논문집
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• pp.801-802
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• 2007

• 인지과학
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• 제10권4호
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• pp.71-83
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• 1999

기존의 기호주의 적 추론 시스템은 경직성 문제로 인하여 유연성을 결여하고 있다. 이는 기호주의 적 지식표현 체계가 지식의 유연한 의미구조를 충분히 반영하고 있지 못할 뿐 아니라 추론 방법도 논리를 바탕으로 하기 때문이다. 이러한 문제를 해결하기 위하여, 우리는 최근 인공 신경 망에 기반 한 유연한 지식표현과 추론을 위한 연결주의 적 의미 망(CSN)을 제안한 바 있다. CSN은 인간의 유사성과 연관성에 기반 하여 근사 추론과 상식추론을 수행할 수 있다. 그러나 CSN 모델에서는 상위개념간의 관계를 표현하는 데 있어서 단순한 전향 신경 망을 이용함으로써 상위개념간의 일반적이고 구조화된 관계를 표현하거나 변수의 표현 및 바인딩의 어려움과 같은 문제점이 있었다. CSN모델의 이런 문제점을 해결하기 위해 본 논문에서는 상위개념간의 일반적이고 구조화된 지식표현을 가능하게 하고 추론이 용이한 기호주의 표현 체계와 이 표현 체계 안에서 의미구조를 표현하고 학습할 수 있는 연결주의 학습 모델인 CSN을 결합한 기호-연결주의 통합 시스템 SymCSN(Symbolic CSN)을 제안하고, 실험을 통하여 제안한 시스템이 인간과 유사한 유연한 지식표현과 추론을 위한 모델임을 보인다.

• 산업경영시스템학회지
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• 제27권4호
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• pp.69-76
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• 2004

A framework for knowledge management system has been explored which enables the semantic search of knowledge on the web. Knowledge representation by RDF and RDF schema enables machine cognition of knowledge documents. Dublin core was adopted for structured metadata representation. Thereby, it enables the CBR and rule based reasoning for intelligent knowledge retrieval. Grafting of the WFMS technique unto the KMS facilitates the effective utilization of process knowledge and creation of new knowledge.

• 동의생리병리학회지
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• 제17권5호
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• pp.1151-1156
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• 2003

To obtain both of the fast and complete data entry and the acquisition of reusable data in a Computer-based Patient Record system (CPR), we are building the ontology that is used by the entry supporting agents. Our application domain is Traditional Chinese Medicine. As the tool for the implementation, we used protege 2000 which is ontology building tool and provides frame knowledge representation language. In this paper, the construction methodology of our ontology is reported.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2008년도 정기 학술대회
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• pp.435-441
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• 2008

Building Information Modelings(BIM) are more complex than typically required for early phase of the design process of a building. Construction projects have many participants from various disciplines involved throughout the entire process. Therefore the success of the project greatly depend on the efficiency of decision-making using the information generated from each process stage. This research utilized an ontology to provide an underlying structure of objects and relationships of a building. The OWL is introduced as a main vehicle to encode the information and knowledge about the building structures and spaces. A case study was conducted to develop a structured representation of an ontology where the relationships among the necessary components in the stage of preliminary design were to be automatically utilized to plan on the sizes of each room in a building and structured thoroughly with a simple structured representation.

• 한국디지털정책학회:학술대회논문집
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• 한국디지털정책학회 2005년도 춘계학술대회
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• pp.545-555
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• 2005

본 연구는 학습 부진아 진단 지식을 온톨로지로 표현함으로써 교사와 학생 간에 발생하는 학습 용어의 불일치성을 해소할 수 있으며 진단 과정에 있어 학습 부진아의 정보를 기반으로 한 추론을 기능하도록 한다. 또한 특정한 진단을 보여주는 일반적인 학습부진아 진단시스템과는 달리, 이러한 지식베이스를 이용하여 사용자에게 정확한 개념어(정답어)를 습득하게끔 해주고, 사용자의 인지 체계 속에 내포되어 있는 개념적 지식을 더욱 더 표면적으로 확장해 나갈 수 있는 온톨로지를 구축하는 방안을 제시한다.

• 산업경영시스템학회지
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• 제23권55호
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• pp.85-96
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• 2000

This paper describes IDMS, a graph-based modeling system that supports problem structuring. We employs influence diagram as a problem representation tool, that is, a modeling tool. In particular, IDMS is designed as domain-independent shell. Therefore, a modeler can change the contents of the knowledge base to suit his/her own interested domain. Since the knowledge base of IDMS contains both modeling knowledge and domain knowledge, IDMS provides not only the syntactic support for modeling tool, but also the semantic support for problem domain. To apply the method in the real world context, we tested IDMS on the process selection problem in business reengineering, which is typical semi-structured problem.

• 한국도서관정보학회지
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• 제16권
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• pp.129-157
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• 1989

Through this study, some considerations to be taken into account in order to construct the user model for the user friendly system which can provide each individuals user armed with varied intellectual level with the relevant information, can be summarized as follows : (1) The user' ability to use the system and users' subject knowledge, the distribution of the users' level knowledge should be considered for the decision of the typed of interaction between the users and the system. (2) the knowledge of the user models should include the following kinds of knowledge inharmony with one another, 1. Standard user knowledge which represents a general characteristic of user group, 2. individual user knowledge which represents an individual's unique characteristic, 3. Long-term user knowledge which represents the education level and subject background of users, 4. short-term user knowledge which represents the purpose of information science and information need by users (3) As knowledge generation technique, both the implicit method and explicit method should be a n.0, pplied, observation of the system during the interaction, and explicit method generates the knowledge by the user's answering the questions already made by the system. (4) The frame technique as the knowledge representation for the user-modelling in which user-knowledge is represented in a limited situation and in a qualitative aspects, can be recommended. The frame is adequated for the explanation of structured situation, and for the processing the present situation by inferring the previous experiences.

• ETRI Journal
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• 제42권2호
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• pp.239-246
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• 2020

Recently, Linked Open Data has become a large set of knowledge bases. Therefore, the need to query Linked Data using question answering (QA) techniques has attracted the attention of many researchers. A QA system translates natural language questions into structured queries, such as SPARQL queries, to be executed over Linked Data. The two main challenges in such systems are lexical and semantic gaps. A lexical gap refers to the difference between the vocabularies used in an input question and those used in the knowledge base. A semantic gap refers to the difference between expressed information needs and the representation of the knowledge base. In this paper, we present a novel method using an ontology lexicon and dependency parse trees to overcome lexical and semantic gaps. The proposed technique is evaluated on the QALD-5 benchmark and exhibits promising results.