• CELLMED
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• v.13 no.2
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• pp.3.1-3.21
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• 2023

In this study, the drinking culture of the Choseon dynasty is examined with the text frequency analysis technique on the entire 『Choseonwangjosilok (朝鮮王朝實錄)』. This study examined a total of 1,968 volumes and 948 books about 27 kings of Choseon , which spans a total of 518 years, through web crawling on the National Institute of Korean History website. Python 3.8 was used to extract sentences related to alcohol, Rhino 1.4.5 was used for morphological analysis to extract nouns, and Gephi 0.9.2 was used for semantic network analysis. According to 『Choseonwangjosilok (朝鮮王朝實錄)』 about alcohol culture, the results of the analysis are as follow: Alcoholic beverages were more often used in court or in ritual ceremonies rather than those based on specific ingredients or manufacturing methods commonly used by the general public. regarding the ruling class through semantic network analysis l in the 『Choseonwangjosilok (朝鮮王朝實錄)』, the Choseon dynasty was found to be highly associated with political issues related to maintaining the power relations within the Korean royal court system. At times, alcohol was used to maintain personal relationships, while at other times it was seen as an essential item in state ceremonies. It was also used as a highly political means to maintain and strengthen national power.

• Journal of the Korean Society for information Management
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• v.20 no.3
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• pp.241-259
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• 2003

The Basic Semantic Register(BSR) is and official ISO register designed for interoperability among eBusiness and EDI systems. The entities registered in the current BSR are not defined in a machine-understandable way, which renders automatic extraction of structural and relationship information from the register impossible. The purpose of this study is to offer a framework for designing an ontology that can provide semantic interoperability among BSR-based systems by defining data structures and relationships with RDF and OWL, similar meaning by the 'equivalentClass' construct in OWL, the hierachical relationships among classes by the 'subClassOf' construct in RDF schema, definition of any entities in BSR by the 'label' construct in RDF schema, specification of usage guidelines by the 'comment' construct in RDF schema, assignment of classes to BSU's by the 'domain' construct in RDF schema, specification of data types of BSU's by the 'range' construct in RDF schema. Hierarchical relationships among properties in BSR can be expressed using the 'subPropertyOf' in RDF schema. Progress in semantic interoperability can be expected among BSR-based systems through applications of semantic web technology suggested in this study.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.600-608
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• 2017

Recently data growth rates are growing exponentially according to the rapid expansion of internet. Since users need some of all the information, they carry a heavy workload for examination and discovery of the necessary contents. Therefore information retrieval must provide hierarchical class information and the priority of examination through the evaluation of similarity on query and documents. In this paper we propose an Multi-class support vector machines model based clustering for hierarchical document categorization that make semantic search possible considering the word co-occurrence measures. A combination of hierarchical document categorization and SVM classifier gives high performance for analytical classification of web documents that increase exponentially according to extension of document hierarchy. More information retrieval systems are expected to use our proposed model in their developments and can perform a accurate and rapid information retrieval service.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.282-296
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• 2010

OWL is an ontology language for the Semantic Web, and suited to modelling the knowledge of a specific domain in the real-world. Ontology also can infer new implicit knowledge from the explicit knowledge. However, the modeled knowledge cannot be complete as the whole of the common-sense of the human cannot be represented totally. Ontology do not concern handling nonmonotonic reasoning to detect incomplete modeling such as the integrity constraints and exceptions. A default rule can handle the exception about a specific class in ontology. Integrity constraint can be clear that restrictions on class define which and how many relationships the instances of that class must hold. In this paper, we propose a practical reasoning system for open and closed-world reasoning that supports a novel hybrid integration of ontology based on open world assumption (OWA) and non-monotonic rule based on closed-world assumption (CWA). The system utilizes a method to solve the problem which occurs when dealing with the incomplete knowledge under the OWA. The method uses the answer set programming (ASP) to find a solution. ASP is a logic-program, which can be seen as the computational embodiment of non-monotonic reasoning, and enables a query based on CWA to knowledge base (KB) of description logic. Our system not only finds practical cases from examples by the Protege, which require non-monotonic reasoning, but also estimates novel reasoning results for the cases based on KB which realizes a transparent integration of rules and ontologies supported by some well-known projects.

• The Journal of Korean Association of Computer Education
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• v.11 no.2
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• pp.55-64
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• 2008

Even though studies on improvement of programming language teaching and learning have been made continuously and many education courseware for programming languages have been developed, computer programming learners' performance is relatively poor. Thus, in this paper, we designed and realized a web- based visual programming learning system by applying cognitive apprenticeship model to improve effect of computer programming education and then put this system into practice in class. As a result, we suggested that it can have positive influence upon learners' performance and their attitude.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1195-1214
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• 2018

Typical search engines may not be the most efficient means of returning images in accordance with user requirements. With the help of semantic web technology, it is possible to search through images more precisely in any required domain, because the images are annotated according to a custom-built ontology. With appropriate annotations, a search can then, return images according to the context. This paper reports on the design of a tourism ontology relevant to touristic images. In particular, the image features and the meaning of the images are described using various properties, along with other types of information relevant to tourist attractions using the OWL language. The methodology used is described, commencing with building an image and tourism corpus, creating the ontology, and developing the search engine. The system was tested through a case study involving the western region of Thailand. The user can search specifying the specific class of image or they can use text-based searches. The results are ranked using weighted scores based on kinds of properties. The precision and recall of the prototype system was measured to show its efficiency. User satisfaction was also evaluated, was also performed and was found to be high.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.723-724
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• 2022

지난 코로나 상황 동안 비대면 수업을 진행했고, 학생들은 빠르게 적응했다. 온라인 수업은 학습자가 이해될 때까지 반복 학습이 가능하고, 시간과 공간의 제약 없이 자기 주도적으로 학습할 수 있다는 장점이 있지만, 온라인상이라는 특징 때문에 교수자와 학습자 간 상호작용이 부족하다는 한계점이 존재한다. 하지만 이점은 차후에 비대면 수업의 지속적인 활용 및 확대를 제한하는 요인이 될 수 있다. 본 논문에서는 상호작용을 높일 수 있는 웹 기반 에듀테크 시스템을 제안한다. 온라인 수업의 강의 영상을 세부적인 내용을 나누는 Section을 통해 다른 학생들이 질문했던 Q&A 데이터를 모아서 생성된 Section-FAQ를 열람할 수 있고, 그 Q&A에 반응해서 상호작용이 가능하다. 또한 교수자에게 Q&A를 보낼 때 영상의 Section 정보와 강의시간 정보를 같이 전송하여 강의 영상을 확인하지 않고, 빠른 답변이 가능하도록 설계했다. 본 논문에서 제안하는 온라인 수업의 상호작용 향상을 위한 웹 기반 에듀테크 시스템을 통해 온라인상에서 교수자의 역할을 대신해주고 비대면 수업의 단점을 해소해주면서, 교수자과 학습자 간의 상호작용을 높여 수업의 이해도를 높이고 학습자들의 학업성취를 높일 수 있을 것이다.

• IE interfaces
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• v.18 no.1
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• pp.10-21
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• 2005

With the increasing proliferation of World Wide Web, electronic mail systems have become very widely used communication tools. Researches on e-mail classification have been very important in that e-mail classification system is a major engine for e-mail response management systems which mine unstructured e-mail messages and automatically categorize them. In this research we compare the performance of Naive Bayesian learning and Centroid-Based Classification using the different data set of an on-line shopping mall and a credit card company. We analyze which method performs better under which conditions. We compared classification accuracy of them which depends on structure and size of train set and increasing numbers of class. The experimental results indicate that Naive Bayesian learning performs better, while Centroid-Based Classification is more robust in terms of classification accuracy.

• International Journal of Computer Science & Network Security
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• v.23 no.8
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• pp.168-176
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• 2023

The use of sensors and actuators as a form of controlling cyber-physical systems in resource networks has been integrated and referred to as the Internet of Things (IoT). However, the connectivity of many stand-alone IoT systems through the Internet introduces numerous security challenges as sensitive information is prone to be exposed to malicious users. In this paper, IoT based-security issues ontology is proposed to collect, examine, analyze, prepare, acquire and preserve evidence of IoT security issues challenges. Ontology development has consists three main steps, 1) domain, purpose and scope setting, 2) important terms acquisition, classes and class hierarchy conceptualization and 3) instances creation. Ontology congruent to this paper is method that will help to better understanding and defining terms of IoT based-security issue ontology. Our proposed IoT based-security issue ontology resulting from the protégé has a total of 44 classes and 43 subclasses.

• The Journal of Korean Association of Computer Education
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• v.9 no.6
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• pp.29-39
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• 2006

The Web is evolving quantitatively into an explosive development. However, users usually have heavy burden of searching information because of the absence of contextual meaning on the Web. Due to an enormous amount of information, users have to endure for finding strong cohesive keywords by themselves and read each of the documents with enduring effort. This paper proposes an efficient method of searching more relative documents than current KEM-based searching systems on the Web by using contextual meaning. We designed a domain ontology on computer hardware, and a searching system which was searching those e-Learning objects. Owing to the Ontology-applied search system, information such as educational materials and related multimedia can be easily provided to the users. Further, learners could be informed of relationship of knowledge, e.g., class hierarchy, properties and values, and so on. The request results are semantically related to users' needs, and thus the system provides a learner-centered searching.