• Journal of Physiology & Pathology in Korean Medicine
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• v.30 no.6
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• pp.402-411
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• 2016

The concept of the meridian system is originated from an empirical, systematic references in the clinical setting, which does not always require anatomical features. As the principles of systems biology are mainly associated with regulating the body's internal environment to maintain a stable condition, they are closely similar to the theory of the meridian system. In this review, I describe the origin of the concept of the meridian system, current status of research on the meridian system and acupuncture points, and the future directions of the research. To unravel the entity of the meridian system, we have to start from understanding its origin and clinical significance. The meridian system, as a theoretical model of the indications of acupuncture points, can help to understand the interconnections that underlie the pathologies of particular diseases or symptoms. Based on the establishment of clinical data platform for acupuncture research, we can extract novel medical information from the clinical data and generate analytical models that are useful for medical knowledge discovery on acupuncture points in the future.

• Genomics & Informatics
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• v.17 no.2
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• pp.17.1-17.3
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• 2019

Text mining has become an important research method in biology, with its original purpose to extract biological entities, such as genes, proteins and phenotypic traits, to extend knowledge from scientific papers. However, few thorough studies on text mining and application development, for plant molecular biology data, have been performed, especially for rice, resulting in a lack of datasets available to solve named-entity recognition tasks for this species. Since there are rare benchmarks available for rice, we faced various difficulties in exploiting advanced machine learning methods for accurate analysis of the rice literature. To evaluate several approaches to automatically extract information from gene/protein entities, we built a new dataset for rice as a benchmark. This dataset is composed of a set of titles and abstracts, extracted from scientific papers focusing on the rice species, and is downloaded from PubMed. During the 5th Biomedical Linked Annotation Hackathon, a portion of the dataset was uploaded to PubAnnotation for sharing. Our ultimate goal is to offer a shared task of rice gene/protein name recognition through the BioNLP Open Shared Tasks framework using the dataset, to facilitate an open comparison and evaluation of different approaches to the task.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.55-62
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• 2022

A smart tourism chatbot is needed as a user interface to efficiently provide smart tourism services such as recommended travel products, tourist information, my travel itinerary, and tour guide service to tourists. We have been developed a smart tourism app and a smart tourism information system that provide smart tourism services to tourists. We also developed a smart tourism chatbot service consisting of khaiii morpheme analyzer, rule-based intention classification, and tourism information knowledge base using Neo4j graph database. In this paper, we develop the Korean and English smart tourism Name Entity (NE) datasets required for the development of the NER model using the pre-trained language models (PLMs) for the smart tourism chatbot system. We create the tourism information NER datasets by collecting source data through smart tourism app, visitJeju web of Jeju Tourism Organization (JTO), and web search, and preprocessing it using Korean and English tourism information Name Entity dictionaries. We perform training on the KoBERT-CRF NER model using the developed Korean and English tourism information NER datasets. The weight-averaged precision, recall, and f1 scores are 0.94, 0.92 and 0.94 on Korean and English tourism information NER datasets.

• Journal of the Korean Operations Research and Management Science Society
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• v.14 no.2
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• pp.27-42
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• 1989

REA (Restricted Entity Aspect) model is a knowledge representation model to classify the aspect type, the EA model component, into five aspects (IS-A-aspect, A-PART-OF aspect, attribute aspect, role aspect, and operation aspect). EATPS, the knowledge representation system, consists of user interface module, knowledge creation module, instance management module, schema management module, and integrity checking module. EATPS creates and manages interactively REA model based knowledge base. This paper shows the structure and functions of EATPS, the design and interactive construction of the knowledge definition language EAKDL, the functions and algorithm of class creation module, and the functions and algorithm of instance creation module to include inheritance inference mechanism.

• Journal of the Korea Society of Computer and Information
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• v.22 no.4
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• pp.99-105
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• 2017

Plato and Aristotle examined what the true spirit of physical education is and what kind of relationship it is, from the perspective of dividing into two parts of the body and mind. And the relationship between human body and mind, knowledge and behavior. Plato and Aristotle examined the harmonious combination of body and mind and what is the desirable relationship setting. In Plato's soul and body in philosophical centered ideological aspect, human education center emphasizes poetry education, but physical education is recognized as essential education for human education. Plato's body contour emphasizes the harmony of soul and body, not the superiority of the body to the mind. In Plato's education room, physical education should be preceded and then mental education should be done. I thought that there could be no independent souls without bodies. It is not an independent entity but a unified entity. Because there is a body, there is a soul. There is a soul, so a body exists. Aristotle thought that the body was more important than Plato, and that the body should be preceded by the soul.

• The Journal of Information Technology and Database
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• v.6 no.2
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• pp.45-57
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• 1999

This paper makes an attempt to find a systematic portion of the database design process, especially using the Entity-Relationship(E-R) model. Basically, we consider three aspects as a systematic portion of the database design process. They are, the strategy that a designer selects to design an E-R diagram, designer's cognitive style, and the knowledge and preference of the database designer. An experiment has been carried out in order to verify the systematic relationship between above-mentioned three aspects and the E-R modeling performance. The target system is a professional baseball system. A normative E-R diagram was constructed based upon 48 E-R diagrams produced during the experiment. The ANOVA process has been used to analyze the results. It has been found that there exist significant differences in query-answering capacity and the completeness of the E-R model among design methods. Individual differences in cognitive styles has not been found to be significantly related to the modeling performance.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.4
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• pp.108-117
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• 2015

In this paper, as a previous step of software development, through an analysis step in the basic design process of the FPSO crane, ERD, which could help develop common understanding between its developer and the user, was introduced. From the flowchart of the design process, the overall work flow in its development was understood. Then, after the design process of the crane was divided into many entities, the attributes of each entity were defined and the relationships between the entities were established, followed by ERD creation through the use of IDEF1X notation. The results of the analysis can be readily understood even by users who lack of software knowledge, and then their change requirements can be immediately reflected in the developed system that requires modification.

• The Journal of Information Technology and Database
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• v.1 no.2
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• pp.3-24
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• 1994

기존의 데이타 모델 및 설계 방법론들은 실세계의 데이타 객체에 대해 고정된 한 측면의 모델 표현만을 허용하기 때문에 여러 측면으로 관측이 가능한 실세계 객체들의 표현에 어려움을 갖는다. 제시한 객체 중심 측면 모델(OOAM : Object-Oriented Entity Aspect Model)은 실세계의 각 객체에 대해 다수의 측면 표현을 가능하게 한 객체 중심의 데이타 모델로 데이타와 지식 표현에 유용한 모델이다. 데이타베이스 시스템과 지식베이스 시스템 중 어느 하나의 시스템이 다른 시스템의 특징을 빌리거나 통합할 수 있다면 두 시스템에게 서로 이득이 될 수 있다. 이러한 KB/DB(Knowledge Base/Data Base)의 통합은 최근에 객체 지향 개념과 연역 개념에 의해 연구가 활발히 진행되고 있다. 본 논문에서는 객체의 측면 개념을 제공하는 OOAM의 기본 개념을 보여주고 OOAM에 의해 구축되는 데이타베이스 스키마의 시맨틱을 분석하고 서술하기 위해 OOAM을 형식적으로 정의하였다. 그리고 KB/DB 통합에 관련된 연구들을 분석하고 데이타베이스에 관련된 지식의 종류를 서술한 후 OOAM을 사용하여 KB/DB 통합을 위한 지식베이스와 데이타베이스의 개발 방법론을 제시하였다.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.4
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• pp.492-496
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• 2010

Wikipedia as an open encyclopedia contains immense human knowledge written by thousands of volunteer editors and its reliability is also high. In this paper, we propose to automatically construct a Korean named entity dictionary using the several features of the Wikipedia. Firstly, we generate class hierarchies using the class information from each article of Wikipedia. Secondly, the titles of each article are mapped to our class hierarchies, and then we calculate the entropy value of the root node in each class hierarchy. Finally, we construct named entity dictionary with high performance by removing the class hierarchies which have a higher entropy value than threshold. Our experiment results achieved overall F1-measure of 81.12% (precision : 83.94%, recall : 78.48%).

• Journal of Digital Convergence
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• v.12 no.6
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• pp.245-252
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• 2014

Semantic search promises to provide more accurate result than present-day keyword matching-based search by using the knowledge base represented logically. But, the ordinary users don't know well the complex formal query language and schema of the knowledge base. So, the system should interpret the meaning of user's keywords. In this paper, we describe a user query interpretation system for the semantic retrieval of multimedia contents. Our system is ontological knowledge base-driven in the sense that the interpretation process is integrated into a unified structure around a knowledge base, which is built on domain ontologies.