• Journal of Korea Trade
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• v.26 no.8
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• pp.37-57
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• 2022

Purpose -International diplomacy is key for the cohesive economic growth of countries around the world. This study aims to identify the major topics discussed and make sense of word pairs used in sentences by Chinese senior leaders during their diplomatic visits. It also compares the differences between key topics addressed during diplomatic visits to developed and developing countries. Design/methodology - We employed three methods: word frequency, co-word, and semantic network analysis. Text data are crawling state and official visit news released by the Ministry of Foreign Affairs of the People's Republic of China regarding diplomatic visits undertaken from 2015-2019. Findings - The results show economic and diplomatic relations most prominently during state and official visits. The discussion topics were classified according to nine centrality keywords most central to the structure and had the maximum influence in China. Moreover, the results showed that China's diplomatic issues and strategies differ between developed and developing countries. The topics mentioned in developing countries were more diverse. Originality/value - Our study proposes an effective approach to identify key topics in Chinese diplomatic talks with other countries. Moreover, it shows that discussion topics differ for developed and developing countries. The findings of this research can help researchers conduct empirical studies on diplomacy relationships and extend our method to other countries. Additionally, it can significantly help key policymakers gain insights into negotiations and establish a good diplomatic relationship with China.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.47-64
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• 2021

The global spread of COVID-19 around the world has not only affected many parts of our daily life but also has a huge impact on many areas, including the economy and society. As the number of confirmed cases and deaths increases, medical staff and the public are said to be experiencing psychological problems such as anxiety, depression, and stress. The collective tragedy that accompanies the epidemic raises fear and anxiety, which is known to cause enormous disruptions to the behavior and psychological well-being of many. Long-term negative emotions can reduce people's immunity and destroy their physical balance, so it is essential to understand the psychological state of COVID-19. This study suggests a method of monitoring medial news reflecting current days which requires striving not only for physical but also for psychological quarantine in the prolonged COVID-19 situation. Moreover, it is presented how an easier method of analyzing social media networks applies to those cases. The aim of this study is to assist health policymakers in fast and complex decision-making processes. News plays a major role in setting the policy agenda. Among various major media, news headlines are considered important in the field of communication science as a summary of the core content that the media wants to convey to the audiences who read it. News data used in this study was easily collected using "Bigkinds" that is created by integrating big data technology. With the collected news data, keywords were classified through text mining, and the relationship between words was visualized through semantic network analysis between keywords. Using the KrKwic program, a Korean semantic network analysis tool, text mining was performed and the frequency of words was calculated to easily identify keywords. The frequency of words appearing in keywords of articles related to COVID-19 emotions was checked and visualized in word cloud 'China', 'anxiety', 'situation', 'mind', 'social', and 'health' appeared high in relation to the emotions of COVID-19. In addition, UCINET, a specialized social network analysis program, was used to analyze connection centrality and cluster analysis, and a method of visualizing a graph using Net Draw was performed. As a result of analyzing the connection centrality between each data, it was found that the most central keywords in the keyword-centric network were 'psychology', 'COVID-19', 'blue', and 'anxiety'. The network of frequency of co-occurrence among the keywords appearing in the headlines of the news was visualized as a graph. The thickness of the line on the graph is proportional to the frequency of co-occurrence, and if the frequency of two words appearing at the same time is high, it is indicated by a thick line. It can be seen that the 'COVID-blue' pair is displayed in the boldest, and the 'COVID-emotion' and 'COVID-anxiety' pairs are displayed with a relatively thick line. 'Blue' related to COVID-19 is a word that means depression, and it was confirmed that COVID-19 and depression are keywords that should be of interest now. The research methodology used in this study has the convenience of being able to quickly measure social phenomena and changes while reducing costs. In this study, by analyzing news headlines, we were able to identify people's feelings and perceptions on issues related to COVID-19 depression, and identify the main agendas to be analyzed by deriving important keywords. By presenting and visualizing the subject and important keywords related to the COVID-19 emotion at a time, medical policy managers will be able to be provided a variety of perspectives when identifying and researching the regarding phenomenon. It is expected that it can help to use it as basic data for support, treatment and service development for psychological quarantine issues related to COVID-19.

• Proceedings of the Korean Institute of Landscape Architecture Conference
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• 2007.10b
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• pp.78-83
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• 2007

The colors have a close to our life and there are many color names derived from plants in Japan. This study aimed to analyze relationship people and plants and investigated what the images of colors derived from plants related to the color names. Surveys on color images of abstract and concrete were conducted with adults who lived in the metropolitan area and in urban areas. The subjects were surveyed about images of similar colors derived from plants(3 type of similar two colors; pink, green and yellow) and asked to select a pair of color names(momo or pink, midori or green, yamabuki or lemon) corresponding to the color. The subjects were simultaneously presented with two similar colors and asked to give their perceptions of each color against 13 polar opposite pairs of terms or phrases using a Semantic Differential Scale, and asked to select the number of the 16 items concerned with life such as clothes and food. With the pink colors, many subjects did not feel opposite abstract images between these two similar colors and felt the same concrete images such as 'cosmetics' and 'clothes', and these color names such as momo and pink are confused. With the green colors and the yellow colors, many subjects felt opposite abstract images between these two similar colors such as 'natural - artificial' and 'rural - urban' and different concrete images such as 'plants' and 'plastics', and these two similar colors are distinguished by the color names such as 'midori - green' and 'yamabuki - lemon'. The results revealed that there are two patterns in the relationship colors derived from plants, color images and color names. In the pattern which images of colors derived from plants are connected with artificial things irrelevant to plants, the color names corresponding to the two similar colors are confused. On the other hand, in the pattern which images of colors derived from plants are connected with plants and artificial things, the two similar colors are distinguished by their color names. So demographics influenced the images of color, younger subjects compared with older tend to obviously distinguish images of colors derived from plants, and there are images of color influenced by the environment as a child. In both patterns, images of colors derived from plants are influenced by artificial things and natural colors are limited among many people. These results indicate that there are a few opportunities to see colors of plants which are full of variety. These results suggest that it is necessary to recognize colors derived from plants in relation to plants and to educate regarding the nature of plants, therefore landscape architecture focused on colors of plants is required.

• The Journal of the Korea Contents Association
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• v.14 no.1
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• pp.364-373
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• 2014

The relationship between a service provided via the information system and user satisfaction has been thought of as an important factor for the development of a new service for the information system. In this study, the twelve new key services that are applicable to national R&D report system were derived by web environment changes in step with IT technology developments in order to support the new service for the user. The twelve new key services are as follows; semantic search service for national R&D report, associated report service, RSS service, mesh-up service, topic-map service, open API service, personalized service, collective intelligence service, SNS service, unstructured data service, detailed search service, mailing service. To assess the quality attribute of the twelve new key services in the national R&D report system, a survey was performed. In conclusion, a stepwise service plan for the national R&D report system was proposed which would use the satisfaction coefficient and the results of the service classification. The following step-by-step service should be developed by in this way. The unstructured data service, personalized service, associated report service, topic-map service, open API service, and the collective intelligence service are needed to develop the first step and RSS service, mesh-up service, semantic search service for the national R&D report, mailing service, detailed search service, and SNS service are needed to develop the second step.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.1-10
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• 2017

Open data has received a lot of attention from around the world. The Korean government is also making efforts to open government data. However, despite the quantitative increase in public data, the lack of data is still pointed out. This paper proposes a method to improve data sharing and utilization by semantically linking public data. First, we propose a knowledge model for expressing administrative districts and their semantic relationships in Korea. An administrative district is an administrative unit that divides the territory of a nation, which is a unit of politics, according to the purpose of the state administration. The knowledge model of the administrative district defines the structure of the administrative district system and the relationship between administrative units based on the Local Autonomy Act. Second, a knowledge graph of the administrative districts is introduced. As a reference information to link public open data at a semantic level, some characteristics of a knowledge graph of administrative districts and methods for linking heterogeneous public open data and improving data quality are addressed. Finally, some use cases are addressed for interlinking between the knowledge graph of the administrative districts and public open data. In particular, national administrative organisations are interlinked with the knowledge graph, and it demonstrates how the knowledge graph can be utilised for improving data identification and data quality.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.835-845
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• 2013

Association rule of data mining techniques is the method to quantify the relevance between a set of items in a big database, andhas been applied in various fields like manufacturing industry, shopping mall, healthcare, insurance, and education. Philosophers of science have proposed interestingness measures for various kinds of patterns, analyzed their theoretical properties, evaluated them empirically, and suggested strategies to select appropriate measures for particular domains and requirements. Such interestingness measures are divided into objective, subjective, and semantic measures. Objective measures are based on data used in the discovery process and are typically motivated by statistical considerations. Subjective measures take into account not only the data but also the knowledge and interests of users who examine the pattern, while semantic measures additionally take into account utility and actionability. In a very different context, researchers have devoted a lot of attention to measures of confirmation or evidential support. The focus in this paper was on asymmetric confirmation measures, and we compared confirmation measures with basic association thresholds using some simulation data. As the result, we could distinguish the direction of association rule by confirmation measures, and interpret degree of association operationally by them. Futhermore, the result showed that the measure by Rips and that by Kemeny and Oppenheim were better than other confirmation measures.

• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.247-260
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• 2003

To share and standardize information, especially in the database environments, MDR (Metadata Registry) can be used to integrate various heterogeneous databases within a particular domain. But due to the discrepancies of data element representation between organizations, global information integration is not so easy. And users who are searching integrated information on the Web have limitation to obtain schema information for the underlying source databases. To solve those problems, in this paper, we present a 3-layered Information Integration System (LI2S) based on MDRs and Ontology. The purpose of proposed architecture is to define information integration model, which combine both of the nature of MDRs standard specification and functionality of ontology for the concept and relation. Adopting agent technology to the proposed model plays a key role to support the hierarchical and independent information integration architecture. Ontology is used as for a role of semantic network from which it extracts concept from the user query and the establishment of relationship between MDRs for the data element. (MDR and Knowledge Base are used as for the solution of discrepancies of data element representation between MDRs. Based on this architectural concept, LI2S was designed and implemented.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.231-238
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• 2021

SNS data can catch the user's thoughts and actions. And the trend of the search portal is a representative service that can observe the interests of users and their changes. In this paper, the relationship was analyzed by comparing statistics on narcotics incidents and the degree of exposure to narcotics related words in tweets of SNS and in the trends of search portal. It was confirmed that the trend of SNS and search portal trends was the same in the statistics of the prosecution office with a certain time difference.In addition, cluster analysis was performed to understand the meaning of tweets in which narcotics related words were mentioned. In the 50,000 tweets collected in January 2020, it was possible to find meaning related to the sale of actual drugs. Therefore, through SNS monitoring alone it is possible to monitor narcotics-related incidents and to find specific sales or purchase-related information, and this can be used in the investigation process. In the future, it is expected that crime monitoring and prediction systems can be proposed as related crime analysis may be possible not only with text but also images.

• 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.

• Korean Journal of Heritage: History & Science
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• v.56 no.2
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• pp.28-45
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• 2023

Although we have entered the era of digital transformation, there is currently no system that efficiently collects, manages, integrates, and services a large number of archaeological digital source materials produced as a result of cultural relics research, i.e., an intelligent integrated management and service platform for archaeological academic information. In this regard, the need to build a digital dictionary of Korean archaeology was confirmed by examining the problem of the Digital Encyclopedia of Korean Archaeology, which is currently available in PDF format on the web, the current status of the publication and use of the Dictionary of Korean Archaeology, and the cases of building digital platforms at home and abroad. Therefore, this paper aims to suggest a general direction for creating a digital encyclopedia of Korean archaeology based on the Dictionary of Korean Archaeology, which includes quality knowledge information, to reconsider the accessibility of archaeological data in conformity with data access limitations. The application of the series Dictionary of Korean Archaeology, published since 2001, and the necessity for digital transformation were examined, as well as the application of data from the archaeological data archiving platforms of Europe, the USA, Japan, and cases of establishing platforms corresponding to specialized encyclopedias from Korea. Based on these, a three-step implementation plan and detailed projects were suggested to create the Digital Encyclopedia of Korean Archaeology. Through this, we proposed the design of metadata for computerized records and the expansion to semantic (meaning-based) data that gives and shows the relationship information between the produced metadata as the implementation tasks to build the Digital Dictionary of Korean Archaeology. It is hoped that such research will help create an integrated intelligent management and service platform for archaeology, raise awareness, and provide a better understanding of Korean archaeology to the general public.