• Journal of the Korean Society for information Management
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• v.30 no.4
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• pp.195-213
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• 2013

This study aims at establishing the identity of teaching Korean as a Foreign Language (KFL) domain by using journal profiling and co-word analysis in comparison with the relevant and adjacent domains. Firstly, by extracting and comparing topic terms, we calculate the similarity of academic journals of the three domains, KFL, teaching Korean as a Native Language (KNL), and Korean Linguistics (KL). The result shows that the journals of KFL form a distinct cluster from the others. The profiling analysis and co-word analysis are then conducted to visualize the relationship among all the three domains in order to uncover the characteristics of KFL. The findings show that KFL is more similar to KNL than to KL. Finally, the comparison of knowledge structures of these three domains based on the co-word analysis demonstrates the uniqueness of KFL as an independent domain in relation with the other relevant domains.

• Journal of KIISE
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• v.44 no.11
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• pp.1178-1193
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• 2017

It is very important to understand system behaviors in collective pattern for each knowledge domain. However, there are structural limitations to represent collective behaviors because of the size of system components and the complexity of their interactions, causing the state explosion problem. Further composition with other systems is mostly impractical because of exponential growth of their size and complexity. This paper presents a practical method to model the collective behaviors, based on a new concept of domain engineering: behavior ontology. Firstly, the ontology defines each collective behavior of a system from active ontology. Secondly, the behaviors are formed in a quantifiably abstract lattice, called common regular expression. Thirdly, a lattice can be composed with other lattices based on quantifiably common elements. The method can be one of the most innovative approaches in representing system behaviors in collective pattern, as well as in minimization of system states to reduce system complexity. For implementation, a prototype tool, called PRISM, has been developed on ADOxx Meta-Modelling Platform.

• Journal of Information Management
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• v.37 no.3
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• pp.61-84
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• 2006

In this paper, we proposed one of the methods for building thesaurus in Science & Technology domain and investigated its applicability as an inference service based on ontology. There exist as many building methods for thesaurus as its role and function, and actually many thesauri capable of ensuring the accuracy and efficiency in information search are being built by many experts. After examining the previous studies related to the principles of building thesaurus and relevant concept "facet", we focused on its characteristics and applied it to building thesaurus. The facet is classified into 2 categories, conceptual facet and relational facet. The latter contains 3 subcategories: category relational facet, attribute relational facet and thematic relational facet. The thesaurus for Science & Technology domain using facets can be applied as a web-based inference service. As a result, the three types of inference service, COP(Communities of Practice), Researcher Tracing and Research Map are provided by means of ontology, and can be applied for the Query Expansion.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.479-486
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• 2005

The ontology was proposed to construct the logical basis of semantic web. Ontology represents domain knowledge in the formal form and it enables that machine understand domain knowledge and provide appropriate intelligent service for user request. However, the construction and the maintenance of ontology requires large amount of cost and human efforts. This paper proposes an automatic ontology construction method for defining relation between concepts in the documents. The Proposed method works as following steps. First we find concept pairs which compose association rule based on the concepts in domain specific documents. Next, we find pattern that describes the relation between concepts by clustering the context between two concepts composing association rule. Last, find generalized pattern name by clustering the clustered patterns. To verify the proposed method, we extract relation between concepts and evaluate the result using documents set provide by TREC(Text Retrieval Conference). The result shows that proposed method cant provide useful information that describes relation between concepts.

• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.31-45
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• 2005

In this paper, convert in RDF triple and a RDF document through RDF document converters and design metadata schema about a digital camcorder after use Wrapper technology, and acquiring commodity information of a HTML page about the digital camcorder which these papers are defined so as to be different by electronic commerce stores, and is expressed. Save in digital camcorder domain ontology storage that implemented to relational database to DCC knowledge base ontology as convert to OWL Web ontology based on designed metadata schema. Through compare with rdf and DCCKBO, mapping, and inference process, provide to buyers by DCC information of the store that had the commodity purchasing information which is the best, and proposed a dynamic Web ontology guessed to contents of the best commodity purchasing information, and to define domain ontology saved in DCCKBO.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.1-22
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• 2021

An online experiment was conducted to test the subject-knowledge view of relevance theory in order to find evidence of a conceptual basis for relevance. Six experts in Library and Information Science (LIS), nine Master's students of LIS, and twelve non-experts judged the relevance of 14 abstracts within and outside of the LIS domain. Consistency among the judges was calculated by joint-probability agreement (PA) and interclass correlation coefficients (ICC). When using PA to analyze the judgements, non-experts had a higher consensus regardless of the task or division of groups. However, ICC calculations found Master's candidates had a higher level of consensus than non-experts within LIS, although the experts did not; and the agreement rates on the non-LIS task for all groups were only poor to moderate. It was only when the groups were analyzed as two groups (experts including Master's candidates and non-experts) that the expected trend of higher consistency among experts in the LIS task was seen.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.3
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• pp.571-576
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• 2024

Ontologies are created by domain experts, but the same content may be expressed differently by each expert due to different understandings of domain knowledge. Since the ontology standardization is still lacking, multiple ontologies can be exist within the same domain, resulting in a phenomenon called the ontology heterogeneity. Therefore, we propose a novel ontology matching method that combines SCBOW(: Siames Continuois Bag Of Words) and BERT(: Bidirectional Encoder Representations from Transformers) models to solve the ontology heterogeneity issue. Ontologies are expressed as a graph and the SimRank algorithm is used to solve the one-to-many problem that can occur in ontology matching problems. Experimental results showed that our approach improves performance by about 8% over traditional matching algorithm. Proposed method can enhance and refine the alignment technology used in ontology matching.

• The Journal of Korean Association of Computer Education
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• v.9 no.3
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• pp.29-45
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• 2006

The IT(Information Technology) is very important growth power in the knowledge information based society. But there is nothing an educational program or system for putting the computer science education in the primary and secondary school into practice. We can talk this problem because of the national curriculum. This existing state brings to a conclusion not only to the political and administrative support but also to the national curriculum. These internal problems are two. First problem is the content in the computer textbook. And second problem is the connection between the computer science education curriculum of university and that of primary and secondary school. This study analyzed the relation about it. And this study suggested the ideal method for connecting those of them. Finally, the results of this study are two. First result is the necessary to reconstruct the domain knowledge of the computer based on the computer science for getting the identity. And second result is necessary to connect between the domain knowledge of the computer based on the computer science identity of university and that of primary and secondary school.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.125-130
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• 2022

최근 자연어처리 연구로 지식 기반 대화에서 대화 내용에 자유로운 주제와 다양한 지식을 포함하는 연구가 활발히 이루어지고 있다. 지식 기반 대화는 대화 내용이 주어질 때 특정 지식 정보를 포함하여 이어질 응답을 생성한다. 이때 대화에 필요한 지식이 검색 가능하여 선택에 제약이 없는 오픈 도메인(Open-domain) 지식 기반 대화가 가능하도록 한다. 오픈 도메인 지식 기반 대화의 성능 향상을 위해서는 대화에 이어지는 자연스러운 답변을 연속적으로 생성하는 응답 생성 모델의 성능 뿐만 아니라, 내용에 어울리는 응답이 생성될 수 있도록 적합한 지식을 선택하는 지식 검색 모델의 성능 향상도 매우 중요하다. 본 논문에서는 오픈 도메인 지식 기반 한국어 대화에서 지식 검색 성능을 높이기 위해 밀집 벡터 기반 검색 방식과 주제어(Keyword) 기반의 검색 방식을 함께 사용하는 것을 제안하였다. 먼저 밀집 벡터 기반의 검색 모델을 학습하고 학습된 모델로부터 고난도 부정(Hard negative) 지식 후보를 생성하고 주제어 기반 검색 방식으로 고난도 부정 지식 후보를 생성하여 각각 밀집 벡터 기반의 검색 모델을 학습하였다. 성능을 측정하기 위해 전체 지식 중에서 하나의 지식을 검색했을 때 정답 지식인 경우를 계산하였고 고난도 부정 지식 후보로 학습한 주제어 기반 검색 모델의 성능이 6.175%로 가장 높은 것을 확인하였다.

• The Journal of Korean Medicine
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• v.44 no.1
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• pp.38-55
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• 2023

Objectives: The purpose of this study was to provide direction for future research in the field of Korean medicine by analyzing microbiome based technologies emerging as a new diagnostic and treatment paradigm. Methods: To achieve the purpose of the study intellectual property data was used. After establishing citation network from registered microbiome-related US patents, citation network was analyzed by knowledge persistence-based main path approach to understanding technological trajectories. Furthermore, community detection algorithms were used to quantitatively identifying specific technological domain in a particular time period. Results: Results shows that early technologies in livestock industry contribute most to the recent patents. Knowledge in the patents flow through the path of food and beverage technological domain, and finally are inherited to the recent development of diagnosis, treatment and prevention technic. Conclusions: This study indicate that developing diagnostic tools which can link the composition of microbiome to specific diseases should be given high priority. Researches should lead to novel therapeutic strategies. Specifically, improving reliability of pattern identification and finding effective therapeutic compositions based on principles of Korean medicine is necessary.