• Journal of the Architectural Institute of Korea Planning & Design
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• v.35 no.7
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• pp.101-108
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• 2019

In this research, I conducted a semantic network analysis centering on media articles on purchasing, revitalizing, and utilizing the former Busan branch of Hansung Bank, a modern architectural heritage. We sought the most efficient analysis elements for the analysis of the social arguments about preservation and utilization embedded in media articles. For this reason, Degree Centrality measures how many connections the word described in the media article has, and Betweenness Centrality measures the influence that controls the flow of information through correlation I examined. In addition, keyword that express the theme well examined the aggregation structure in each sub-network. In this research, in theoretical terms, it makes sense in that the social discussion embedded in the article of the mass media is grasped empirically through semantic network analysis of words. Methodological aspect is best when it includes nouns and adjectives and the distance between words is more than four words in the analysis of the cohesive structure of the semantic network to determine whether the influence of social discussions is best assessed through the connection between words to media articles.

• Journal of the Korea Convergence Society
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• v.12 no.7
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• pp.53-60
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• 2021

LOD-based recommender systems usually leverage the data available within LOD datasets, such as DBpedia, in order to recommend items(movies, books, music) to the end users. These systems use a semantic similarity algorithm that calculates the degree of matching between pairs of Linked Data resources. In this paper, we proposed a new approach to measuring semantic distance in an LOD-based recommender system by assigning weights converted from user ratings to links in the LOD graph. The semantic distance measurement model proposed in this paper is based on a processing step in which a graph is personalized to a user through weight calculation and a method of applying these weights to LDSD. The Experimental results showed that the proposed method showed higher accuracy compared to other similar methods, and it contributed to the improvement of similarity by expanding the range of semantic distance measurement of the recommender system. As future work, we aim to analyze the impact on the model using different methods of LOD-based similarity measurement.

• Education of Primary School Mathematics
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• v.25 no.4
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• pp.361-375
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• 2022

In this study, the vocabularies in elementary mathematics textbooks for grade 1-2 were analyzed according to 9-degree of semantic system. Also, the types of vocabulary were analyzed using general academic words, mathematics specific concept words, and mathematics general concept words. As a result, percentages of 1-degree and 2-degree vocabulary was the most in both grade 1 and 2 mathematics textbooks. It also shows that some of general academic words were 3-degree vocabulary and some of mathematics specific concept words were either unregistered or 1-degree vocabulary. In particular, general academic words, which are 3-degree vocabulary, may be unfamiliar to 1^st and 2^nd grade students. Therefore, students should be given the opportunity to guess and understand the contextual meaning of general academic words from the given contexts in textbooks. The frequency of use of mathematics general concept words in grade 2 textbook increased significantly compared to grade 1 textbook. Since mathematics general concept words are academic and technical vocabulary they should be taught explicitly. Based on the results of this study, implications for vocabulary instruction in mathematics textbooks were discussed.

• The Journal of the Korea Contents Association
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• v.16 no.7
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• pp.179-189
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• 2016

This aim of this study is identify research trends and intellectual structure in the field of Korean journalism and communication studies. For this purpose, a semantic network analysis was employed to analyze keywords in the abstracts of published articles in the Korean Journal of Journalism and Communication Studies from 2005 to 2015. The results showed that "frame", "Twitter", "content analysis" and "social media" are among the most frequently used keywords in the abstracts during this period. With regards to degree and eigenvector centrality, "social capital", "trust" and "twitter" were among the highest. The findings of the periodic characteristics of research trends revealed that there are more studies that employ the traditional media effect theories including Uses and Gratification Theory, Agenda Setting Theory, and Framing Theory before the year of 2010 while those that focus on the specific new media such as smartphones and twitter after 2011. This study has implications in the sense that it can be used as guidelines for making a curriculum or establishing the research system for Korean journalism and communication studies in the future.

• Journal of Digital Convergence
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• v.20 no.2
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• pp.203-215
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• 2022

The study is to investigate research trends and knowledge structures in the Smart Farm field. To achieve the research purpose, keywords and the relationship among keywords were analyzed targeting 104 Korean academic journals related to the Smart Farm in KCI(Korea Citation Index), and topics were analyzed using the LDA Topic Modeling technique. As a result of the analysis, the main keywords in the Korean Smart Farm-related research field were 'environment', 'system', 'use', 'technology', 'cultivation', etc. The results of Degree, Betweenness, and Eigenvector Centrality were presented. There were 7 topics, such as 'Introduction analysis of Smart Farm', 'Eco-friendly Smart Farm and economic efficiency of Smart Farm', 'Smart Farm platform design', 'Smart Farm production optimization', 'Smart Farm ecosystem', 'Smart Farm system implementation', and 'Government policy for Smart Farm' in the results of Topic Modeling. This study will be expected to serve as basic data for policy development necessary to advance Korean Smart Farm research in the future by examining research trends related to Korean Smart Farm.

• Journal of Korean Society of Transportation
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• v.22 no.4 s.75
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• pp.97-106
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• 2004

It is a Known fact that driving through long tunnel increases possibility of traffic accident because of psychological feeling of insecurity and dispersion of drivers' concentration since driving in narrow and limited space for a longtime. It, therefore, results in raising transportation and environment problems, such as traffic accident difficult to be properly dealt with and ventilation. This study aims at proposing a method of augmenting driving amenity by improving the internal lighting facilities in the tunnel. The study is conducted by investigating internal landscapes of tunnels by lighting colors, which are currently being operated. The Color Planning System (CPS), developed by SHARP Co. Ltd, is exploited for selecting adjective that express the sensitivity image on lighting colors. The CPS is an example that applies to sensitivity of human body for products design development. The CPS takes the following process to define the color : 1) expressing "Pvoduct's Image" as "A Word (adjective)" and 2) referring "A Word" to "Image Scale", and 3) determining the color through this "Image Panel". The study is processed by making a questionnaire using the semantic differential (SD) scale, grasping the consciousness structure of experimental persons through the Factor Analysis, and building a model in which dependent variable is "Degree of Preference" about internal landscape in tunnel using LISREL(LInear Structural RELations).