• Journal of the Korean housing association
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• v.17 no.4
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• pp.131-143
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• 2006

Nowadays, diverse mass media discovers and introduces outstanding management cases of apartment complexes to induce vital competitions of constructors and active participation of residents to apartment management. This study statistically analyzed the management issues of outstanding apartment complexes that have been introduced by mass media with lexical criteria to examine the characteristics of their exemplary management. The key issues of outstanding apartment management are summarized as: efficient management of convenient facilities for residents, community activities based on residents' participation, and maintenance of pleasant living environments through transparent management. Also, the result of the relation arrangement of co-occurrence word from a Social Network Analysis included three key concepts of multi-family housing management - Maintenance Management, Operating Management, and Community Life Management - with emphasis on 'residents' and 'apartment complexes.' However, Operating Management was relatively deemphasized.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.24-34
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• 2022

Viewing religion as contents, we analyzed the network structure by creating networks on 13 world religions. The whole network was constructed by combining 13 religions, and it showed the characteristics of a scale-free network as a general social network. The world religion network had a very small value of clustering coefficient, unlike the general social network. This seems to be the result of the diversity of terms that describe religion. The core network was constructed by applying K-core algorithm used to create the core network to the whole network. When k-3 was applied, it was too complicated but when k-4 was applied, it was too simple to obtain meaningful results. It indicates that it difficult to apply the K-core algorithm to a network containing a low clustering coefficient. Therefore, core networks were constructed according to the number of key words centered on the hub node to analyze the characteristics of world religions. In addition, meaningful information was derived by constructing the world's five major religious networks and East Asian religious networks. In this study, various information was obtained by analyzing world religions as contents. It was also presented a method of creating and analyzing a core network based on key words for networks with a low clustering coefficient.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1752-1755
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• 2002

The world wide web (WWW) already accounts f3r more Internee network traffic than any other application, including il and simple file transfer. It is also a collaborative technology in a weak sense of the word - it allows people to share information. Synchronous collaboration is where an interactive activity is simultaneous and in teal-time. Computer based real time collaborative systems like shared whiteboards. collaborative editor etc. are only beginning to emerge recently. These applications invoking more than two users exchanging information, require Multicast communication. Multicast communication is a transmission mode that is now supported by a variety of local and wide area networks. Multicasting enables multiparty communication across a wide area to sparsely distributed groups by minimizing the network load. Multicasting itself is one of the key technologies in the nut generation of the Internet This paper describes the technical issues from the aspect of multicast communication and its reliability in synchronous collaborative application.

• ETRI Journal
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• v.43 no.6
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• pp.1038-1048
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• 2021

We propose an end-to-end neural coreference resolution for the Korean language that uses an attention mechanism to point to the same entity. Because Korean is a head-final language, we focused on a method that uses a pointer network based on the head. The key idea is to consider all nouns in the document as candidates based on the head-final characteristics of the Korean language and learn distributions over the referenced entity positions for each noun. Given the recent success of applications using bidirectional encoder representation from transformer (BERT) in natural language-processing tasks, we employed BERT in the proposed model to create word representations based on contextual information. The experimental results indicated that the proposed model achieved state-of-the-art performance in Korean language coreference resolution.

• Asia pacific journal of information systems
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• v.31 no.1
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• pp.121-140
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• 2021

The main purpose of this research is to understand the strongest predictors of wearable adoption among athletes with an emphasis on the perceived ethics of biometric data. We performed a word co-occurrence study of biometrics research to determine the ethical constructs of biometric data. A questionnaire incorporating the Unified Theory of Acceptance and Use of Technology (UTAUT), Health Belief Model and Biometric Data Ethics was then designed to develop a neural network model to predict the adoption of wearable sensors among athletes. Our model shows that wearable adoption's strongest predictors are perceived ethics, perceived profit, and perceived threat; which can be categorized as professional stressors. The key theoretical contribution of this paper is to extend the literature on UTAUT by developing a predictive modeling of factors affecting acceptance of wearables by athletes, and highlighting the ethical implications of athlete's adoption of wearables.

• Asia pacific journal of information systems
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• v.28 no.1
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• pp.36-60
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• 2018

As an increasing number of people gained access to social network services (SNS), organizations started to use SNS as a channel for marketing and promotional purposes. The online advertising market has significant growth potential. Brand engagement is a key motive for online advertising, but how SNS users engage with brands, particularly in terms of the promotion of organizations, is poorly understood. This study uses customer value theory to examine brand engagement of users in terms of promoting companies in the context of Korean SNS marketing. This study identifies the antecedents of brand engagement based on customer value theory. Our findings show the significance of three factors of SNS marketing, namely, price discount, relationship support, and convenience, on brand engagement. We further show the consequences of brand engagement, namely, purchase decisions and word-of-mouth activities. These findings help advance customer value theory and offer practical insights into the use of information systems and marketing in the context of SNS.

• Journal of Korean Home Economics Education Association
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• v.31 no.4
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• pp.97-113
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• 2019

This study is focused on the examination of changes in textbooks of Home Economics in High school from 7^st to 2015 curriculum, especially the 'Food and Nutrition section. We investigated the content elements of the National Curriculum Guide, the changes in learning contents, and the number of pages of Food and Nutrition section. The key words were extracted and the connective relationships between words were visualized using a method of language network analysis through word cloud and Semantic Network Analysis. According to the results of the research, the portion of the Food and Nutrition section has been gradually decreased on the Technology·Home Economics, following the development of the curriculum. Through the whole curriculum, 'invitation', 'Korean food', 'baby·nutrition' are appeared as key words. The education contents of Food and Nutrition section from the 7^th to 2015 revised have been developed and advanced with the changes of social needs. However, the reduction of portion and insufficiency of content elements of Food and Nutrition section bring concerns toward the decline of the quality of education on dietary life.

• Korean Journal of Social Welfare
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• v.68 no.2
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• pp.185-211
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• 2016

This study analyzes key word networks of the papers which are published at Korean Journal of Social Welfare issued by Korean Academy of Social Welfare from 1979 to 2015. It aims at investigating the trends of social welfare researches in Korea by dividing the given period into two: 1979-2000 and 2001-2015. It shows the trends in three ways: methodologies, subjects, and intellectual structures. In order to identify intellectual structure, it calculate centrality indices basing on co-appearance frequency of key words. It also derives some values which explain relationship structure of key words by using pathfinder algorithm, and finally visualizes the intellectual structures by using the NodeXL program. Some implications of the findings of these analyses are discussed in the end.

• Journal of Fashion Business
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• v.23 no.3
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• pp.85-100
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• 2019

This study examines changes in consumer perceptions of fashion shows, which are critical elements in the apparel industry and a means to represent a brand's image and originality. For this purpose, big data in clothing marketing, text mining, semantic network analysis techniques were applied. This study aims to verify the effectiveness and significance of fashion shows in an effort to give directions for their future utilization. The study was conducted in two major stages. First, data collection with the key word, "fashion shows," was conducted across websites, including Naver and Daum between 2015 and 2018. The data collection period was divided into the first- and second-half periods. Next, Textom 3.0 was utilized for data refinement, text mining, and word clouding. The Ucinet 6.0 and NetDraw, were used for semantic network analysis, degree centrality, CONCOR analysis and also visualization. The level of interest in "models" was found to be the highest among the perception factors related to fashion shows in both periods. In the first-half period, the consumer interests focused on detailed visual stimulants such as model and clothing while in the second-half period, perceptions changed as the value of designers and brands were increasingly recognized over time. The findings of this study can be utilized as a tool to evaluate fashion shows, the apparel industry sectors, and the marketing methods. Additionally, it can also be used as a theoretical framework for big data analysis and as a basis of strategies and research in industrial developments.

• Journal of Fashion Business
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• v.23 no.3
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• pp.51-66
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• 2019

The aim of this study is to identify research trends of "Journal of Fashion Business" by analyzing the keyword network of the paper published between 2006 and 2017. The papers selected for analysis in the study were 287 fashion design articles and 281 fashion marketing articles published between February 2006 and December 2017 and titles, volumes, publishing years, authors, keywords, and abstracts of each paper were collected for data analysis. The research was carried out through selection, collection of article data, keyword extraction and coding, keywords refinement, formation of network matrix, and analysis and visualization process. First, based on the title of the paper used in the analysis, the fashion design/aesthetics, marketing/social psychology, clothing materials, clothing composition, and other fields were classified. Research analysis used the Netminer 4 (Ver.4.3.2) program. Results indicated showed that the intellectual structure of the "Fashion Business" research paper showed key word changes over time, and the degree centrality and between centrality of the keywords.