• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.17-23
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• 2017

The National Competency Standards (NCS) is a standard that allows korea to efficiently organize the training of national talents by systematically classifying the knowledge, skills, and attitudes necessary for the job of industry groups. Ontology is a discipline that allows the abstract information in the human concept to be expressed in a form that enables computing to be done. There is a need to formalize the knowledge management by converting the NCS system currently stored in the simple DB into an ontology. This study design and implement NCS ontology for the task of "Application SW Engineering" among vast NCS jobs, enabling intelligent knowledge management and inference search of the job. In addition, it provides consistency with the formalization specification of the learning contents structure of the competency unit elements of the job, and provides the basis for extension to the whole NCS job ontology.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06a
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• pp.88-90
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• 2006

본 논문에서는 SBML문서를 효율적으로 저장관리 할 수 있는 Gene Ontology 기반의 SBML 문서관리 시스템을 제안한다. SBML은 시스템생물학에서 생화학적 네트워크 데이터의 교환 표준으로 연구 개발되었으며, 다수의 생화학적 네트워크 데이터베이스들이 SBML을 이용하여 데이터를 제공해주고 있다. 이러한 SBML 문서를 통해 서로 다른 데이터베이스 또는 응용 프로그램간 정보를 교환으로 사용되고 있으며, 그 양 또한 급속하게 증가하고 있다. 따라서 본 논문에서는 이러한 대량의 SBML 문서를 효율적으로 저장, 검색 할 수 있는 문서관리시스템을 제안한다. 제안된 시스템은 OODB를 사용하여 효율적으로 SBML 문서를 저장관리하며, Gene Ontology를 기반으로 생화학적 용어의 모호성을 해결하고, SBML문서간의 발생하는 데이터 중복을 제거하여 데이터의 품질을 제고하였다.

• Journal of information and communication convergence engineering
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• v.11 no.3
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• pp.179-184
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• 2013

Traditional clustering methods are usually based on the bag-of-words (BOW) model. A disadvantage of the BOW model is that it ignores the semantic relationship among terms in the data set. To resolve this problem, ontology or matrix factorization approaches are usually used. However, a major problem of the ontology approach is that it is usually difficult to find a comprehensive ontology that can cover all the concepts mentioned in a collection. This paper proposes a new document clustering method using semantic features and fuzzy relations for solving the problems of ontology and matrix factorization approaches. The proposed method can improve the quality of document clustering because the clustered documents use fuzzy relation values between semantic features and terms to distinguish clearly among dissimilar documents in clusters. The selected cluster label terms can represent the inherent structure of a document set better by using semantic features based on non-negative matrix factorization, which is used in document clustering. The experimental results demonstrate that the proposed method achieves better performance than other document clustering methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.5
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• pp.626-631
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• 2007

Autonomous robots performing desired tasks in rough, changing, unstructured environments without continuous human assistance must have the ability to cope with its surroundings whether this be certain or not. The development of algorithms deriving useful conclusions from uncertain information obtained by various sensors may be the first for it. Recently ontology is taken great attention as a method useful for the representation and processing of knowledge. In this paper, we propose an ontology-based navigation algorithm for autonomous robots, and provide computer simulation results in order to show the validity of the proposed algorithm.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.523-530
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• 2014

Ontology alignment is the way to share and reuse of ontology knowledge. Because of the ambiguity of concept, most ontology alignment systems combine a set of various measures and complete enumeration to provide the satisfactory result. However, calculating process becomes more complex and required time increases exponentially since the number of concept increases, more errors can appear at the same time. Lately the focus is on meta-matching using the heuristic algorithm. Existing meta-matching system tune extra parameter and it causes complex calculating, as a consequence, the results in the various data of specific domain are not good performed. In this paper, we propose a high performance algorithm by using DCS that can solve ontology alignment through simple process. It provides an efficient search strategy according to distribution of Levy Flight. In order to evaluate the approach, benchmark data from the OAEI 2012 is employed. Through the comparison of the quality of the alignments which uses DCS with state of the art ontology matching systems.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.617-618
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• 2006

The participants in collaborative environment want to get the right documents which are intended to find. In general search system, it searches documents which contain only the keywords. For searching different word-expressions for the same meaning, we perform mapping before searching. Our mapping logic consists of three steps. First, the character matching is the mapping of two terminologies that have identical character strings. Second, the definition comparing is the method that compares two terminologies' definitions. Third, the similarity checking pairs terminologies which were not mapped by two prior steps. In this paper, we propose Engineering Information Search System based on ontology mapping.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.688-690
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• 2005

Ontology를 이용한 대부분의 이미지 검색 시스템들은 중앙 집중적(Centralization)으로 구성되어 있어, 단일 이미지 제공자의 특정 지식기반의 이미지 검색을 제공한다. 이에 반해 메타데이터 기반의 분산 이미지 검색 시스템들은 이미지 제공자들의 자율성을 보장하기 용의하지만, 지식기반 이미지 검색을 제공하지 못한다. 본 논문은 위 시스템들의 단정들을 극복하기 위해 Web Services를 이용하여 다양한 이미지 제공자들의 자율성을 보장하면서, 지식기반 이미지 검색을 지원하는 프레임워크의 Architecture를 제안한다.

• International Journal of Internet, Broadcasting and Communication
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• v.4 no.2
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• pp.7-11
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• 2012

In this paper, we defined constructivism and ontology theory and associate it in ubiquitous learning. The typical ubiquitous learning involving the Context Aware Intelligent system was presented. Also the Architecture for learning environment including the key idea and technical concept is being presented in this paper. Guided with these principles and with the advancement of information and communication technology the context-awareness based on Artificial intelligence for Location based Service for ubiquitous Learning was conceptualized.

• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.1068-1082
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• 2015

Due to the rapid advancement of the mobile technology, smart phones have been widely used in the current society. This lead to an easier way to retrieve video contents using web and mobile services. However, it is not a trivial problem to retrieve particular video contents based on users' specific preferences. The current movie recommendation system is based on the users' preference information. However, this system does not consider any emotional means or perspectives in each movie, which results in the dissatisfaction of user's emotional requirements. In order to address users' preferences and emotional requirements, this research proposes a movie recommendation technology to represent a movie's emotion and its associations. The proposed approach contains the development of emotion ontology by representing the relationship between the emotion and the concepts which cause emotional effects. Based on the current movie metadata ontology, this research also developed movie-emotion ontology based on the representation of the metadata related to the emotion. The proposed movie recommendation method recommends the movie by using movie-emotion ontology based on the emotion knowledge. Using this proposed approach, the user will be able to get the list of movies based on their preferences and emotional requirements.