• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.453-454
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• 2019

현대 사회에서는 의사 결정을 위해 다양한 도구가 사용되고 있다. 대규모로 진행되는 토의나 토론에서는 데이터를 분석하는데 많은 비용과 시간이 소모되고 있다. 회의록 요약시스템은 기존 문서처리방법을 자동화하여 인건비 절감과 처리시간을 단축하는 긍정적 효과를 기대하고 있다. 본 논문은 기존에 수작업으로 진행되었던 과정을 보다 효과적으로 운영할 수 있도록 회의록 요약시스템을 설계하고 구현한다. 대규모 토론이나 토의에서도 요약시스템 통해 대표의견을 제시받아 정확한 의사결정을 하여 시간절약과 비용절감 효과를 기대한다.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.63-88
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• 2019

The goal of this paper is to investigate changes in North Korea's domestic and foreign policies through automated text analysis over North Korea represented in South Korean mass media. Based on that data, we then analyze the status of text mining research, using a text mining technique to find the topics, methods, and trends of text mining research. We also investigate the characteristics and method of analysis of the text mining techniques, confirmed by analysis of the data. In this study, R program was used to apply the text mining technique. R program is free software for statistical computing and graphics. Also, Text mining methods allow to highlight the most frequently used keywords in a paragraph of texts. One can create a word cloud, also referred as text cloud or tag cloud. This study proposes a procedure to find meaningful tendencies based on a combination of word cloud, and co-occurrence networks. This study aims to more objectively explore the images of North Korea represented in South Korean newspapers by quantitatively reviewing the patterns of language use related to North Korea from 2016. 11. 1 to 2019. 5. 23 newspaper big data. In this study, we divided into three periods considering recent inter - Korean relations. Before January 1, 2018, it was set as a Before Phase of Peace Building. From January 1, 2018 to February 24, 2019, we have set up a Peace Building Phase. The New Year's message of Kim Jong-un and the Olympics of Pyeong Chang formed an atmosphere of peace on the Korean peninsula. After the Hanoi Pease summit, the third period was the silence of the relationship between North Korea and the United States. Therefore, it was called Depression Phase of Peace Building. This study analyzes news articles related to North Korea of the Korea Press Foundation database(www.bigkinds.or.kr) through text mining, to investigate characteristics of the Kim Jong-un regime's South Korea policy and unification discourse. The main results of this study show that trends in the North Korean national policy agenda can be discovered based on clustering and visualization algorithms. In particular, it examines the changes in the international circumstances, domestic conflicts, the living conditions of North Korea, the South's Aid project for the North, the conflicts of the two Koreas, North Korean nuclear issue, and the North Korean refugee problem through the co-occurrence word analysis. It also offers an analysis of South Korean mentality toward North Korea in terms of the semantic prosody. In the Before Phase of Peace Building, the results of the analysis showed the order of 'Missiles', 'North Korea Nuclear', 'Diplomacy', 'Unification', and ' South-North Korean'. The results of Peace Building Phase are extracted the order of 'Panmunjom', 'Unification', 'North Korea Nuclear', 'Diplomacy', and 'Military'. The results of Depression Phase of Peace Building derived the order of 'North Korea Nuclear', 'North and South Korea', 'Missile', 'State Department', and 'International'. There are 16 words adopted in all three periods. The order is as follows: 'missile', 'North Korea Nuclear', 'Diplomacy', 'Unification', 'North and South Korea', 'Military', 'Kaesong Industrial Complex', 'Defense', 'Sanctions', 'Denuclearization', 'Peace', 'Exchange and Cooperation', and 'South Korea'. We expect that the results of this study will contribute to analyze the trends of news content of North Korea associated with North Korea's provocations. And future research on North Korean trends will be conducted based on the results of this study. We will continue to study the model development for North Korea risk measurement that can anticipate and respond to North Korea's behavior in advance. We expect that the text mining analysis method and the scientific data analysis technique will be applied to North Korea and unification research field. Through these academic studies, I hope to see a lot of studies that make important contributions to the nation.

• Journal of the Korean Society for information Management
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• v.36 no.4
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• pp.207-226
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• 2019

Depression is a serious psychological disease that is expected to afflict an increasing number of people. And studies on depression have been conducted in the context of social media because social media is a platform through which users often frankly express their emotions and often reveal their mental states. In this study, large amounts of Korean text were collected and analyzed to determine whether such data could be used to detect depression in users. This study analyzed data collected from Twitter users who had and did not have depressive tendencies between January 2016 and February 2019. The data for each user was separately analyzed before and after the appearance of depressive tendencies to see how their expression changed. In this study the data were analyzed through co-occurrence word analysis, topic modeling, and sentiment analysis. This study's automated data collection method enabled analyses of data collected over a relatively long period of time. Also it compared the textual characteristics of users with depressive tendencies to those without depressive tendencies.

• Journal of the Korean Society for information Management
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• v.39 no.1
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• pp.309-330
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• 2022

Intellectual structure analysis, which quantitatively identifies the structure, characteristics, and sub-domains of fields, has rapidly increased in recent years. Analysis techniques traditionally used to conduct intellectual structure analysis research include bibliographic coupling analysis, co-citation analysis, co-occurrence analysis, and author bibliographic coupling analysis. This study proposes a novel intellectual structure analysis method, Keyword Bibliographic Coupling Analysis (KBCA). The Keyword Bibliographic Coupling Analysis (KBCA) is a variation of the author bibliographic coupling analysis, which targets keywords instead of authors. It calculates the number of references shared by two keywords to the degree of coupling between the two keywords. A set of 1,366 articles in the field of 'Open Data' searched in the Web of Science were collected using the proposed KBCA technique. A total of 63 keywords that appeared more than 7 times, extracted from 1,366 article sets, were selected as core keywords in the open data field. The intellectual structure presented by the KBCA technique with 63 key keywords identified the main areas of open government and open science and 10 sub-areas. On the other hand, the intellectual structure network of co-occurrence word analysis was found to be insufficient in the overall structure and detailed domain structure. This result can be considered because the KBCA sufficiently measures the relationship between keywords using the degree of bibliographic coupling.

• Journal of Korean Society for Quality Management
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• v.45 no.4
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• pp.709-716
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• 2017

Purpose: NCS(National Competency Standards) is a systematic organization of knowledge, skills, and literacy required for performing tasks in industrial settings. This research aims to search for keywords that are important to us and to present key directions of education for the fourth industrial age in the future. Methods: The systematic classification system of NCS was investigated and the classification code structure was analyzed. Among them, the frame and structure analysis of the classification code of quality was analyzed using R-program. Results: This study grasped the quality classification situation of NCS and suggested improvement plan from the operational aspect of the fourth industrial revolution era. Conclusion: In conclusion, this study suggested the idea of education direction of SMEs(Small and Medium-sized Enterprises) in the era of the 4th industrial revolution by understanding NCS which reflects Korean characteristics.

• Journal of Fashion Business
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• v.14 no.5
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• pp.49-65
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• 2010

The purpose of this paper is to derive the categories of negative e-WOM (electronic word of mouth) via consumer review. Disclosing the details of negative e-WOM based consumer reviews has never been done before. For this reason, a content analysis was adopted to provide knowledge and understanding of the phenomenon. This paper analyzes the content of 630 consumer reviews posted on the open market internet site, www.auction.co.kr. The analysis was conducted from October 20th, 2008 to March 10th, 2009. The results indicated that the negative e-WOM based consumer reviews can be divided into two categories: the cognitive evaluation and the expression of consumer's emotion. The category of cognitive evaluation is consisted of negative e-WOM of product, negative e-WOM of service, and warning about the risk of purchasing products. The category of expressing consumers' emotion are composed of venting customers' dissatisfaction and passive response of dissatisfaction. Investigating the details of negative e-WOM has a number of implications. Most importantly, the results revealed multidimensional structure of negative e-WOM. This understanding of negative e-WOM communication allows marketers to improve products and services that better meet customers' current and future needs.

• Geomechanics and Engineering
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• v.32 no.3
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• pp.347-359
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• 2023

With the development of infrastructure, there is a critical shortage of filling materials all over the word. However, a large amount of silt accumulated in the lower reaches of the Yellow River is treated as waste every year, which will cause environmental pollution and waste of resources. Microbial induced calcium carbonate precipitation (MICP) technology, with the advantage of efficient, economical and environmentally friendly protection, is selected to solidify the abandoned Yellow River silt with poor mechanical properties into high-quality filling material in this paper. Based on unconfined compressive strength (UCS) test, determination of calcium carbonate (CaCO₃) content and scanning electron microscope (SEM) test, the effects of cementation solution concentration, treatment times and relative density on the solidification effect were studied. The results show that the loose silt particles can be effectively solidified together into filling material with excellent mechanical properties through MICP technology. The concentration of cementation solution have a significant impact on the solidification effect, and the reasonable concentration of cementation solution is 1.5 mol/L. With the increase of treatment times, the pores in the soil are filled with CaCO₃, and the UCS of the specimens after 10 times of treatment can reach 2.5 MPa with a relatively high CaCO₃ content of 26%. With the improvement of treatment degree, the influence of relative density on the UCS increases gradually. Microscopic analysis revealed that after MICP reinforcement, CaCO₃ adhered to the surface of soil particles and cemented with each other to form a dense structure.

• Journal of the Korean Society for information Management
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• v.38 no.2
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• pp.153-172
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• 2021

This study is to create a deep learning based classification model to examine the characteristics of panic disorder and to classify the panic disorder tendency literature by the panic disorder corpus constructed for the present study. For this purpose, 5,884 documents of the panic disorder corpus collected from social media were directly annotated based on the mental disease diagnosis manual and were classified into panic disorder-prone and non-panic-disorder documents. Then, TF-IDF scores were calculated and word co-occurrence analysis was performed to analyze the lexical characteristics of the corpus. In addition, the co-occurrence between the symptom frequency measurement and the annotated symptom was calculated to analyze the characteristics of panic disorder symptoms and the relationship between symptoms. We also conducted the performance evaluation for a deep learning based classification model. Three pre-trained models, BERT multi-lingual, KoBERT, and KcBERT, were adopted for classification model, and KcBERT showed the best performance among them. This study demonstrated that it can help early diagnosis and treatment of people suffering from related symptoms by examining the characteristics of panic disorder and expand the field of mental illness research to social media.

• Journal of the Korean Society for Library and Information Science
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• v.52 no.1
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• pp.341-357
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• 2018

Due to the paradigm of open science and advanced digital information technology, data sharing and re-use have been actively conducted and considered data-intensive in a wide variety of disciplines. This study aims to investigate the intellectual structure portrayed by the research products re-using the data sets from ICPSR. For the purpose of this study, a total of 570 research products published in 2017 from the ICPSR site were collected and analyzed in two folds. First, the authors and publications of those research products were analyzed in order to show the trends of research using ICPSR data. Authors tend to be affiliated with university or research institute in the United States. The subject areas of journals are recognized into Social Sciences, Health, and Psychology. In addition, a network with clustering analysis was conducted with using co-word occurrence from the titles of the research products. The results show that there are 12 clusters, mental health, tabocco effect, disorder in school, childhood, and adolescence, sexual risk, child injuries, physical activity, violent behavior, survey, family role, women, problem behavior, gender differences in research areas. The structure portrayed by ICPSR data re-uses demonstrates that substantial number of studies in Medicine have been conducted with a perspective of social sciences.

• Korean Journal of Environment and Ecology
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• v.33 no.1
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• pp.9-15
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• 2019

Artiodactyla, which is an even-toed mammal, widely inhabits worldwide. In recent years, wild Artiodactyla species have attracted public attention due to the rapid increase of crop damage and road-kill caused by wild Artiodactyla such as water deer and wild boar and the decrease of some species such as long-tailed goral and musk deer. In spite of such public attention, however, there have been few studies on Artiodactyla in Korea, and no studies have focused on the trend analysis of Artiodactyla, making it difficult to understand actual problems. Many recent studies on trend used text-mining and co-occurrence analysis to increase objectivity in the classification of research subjects by extracting keywords appearing in literature and quantifying relevance between words. In this study, we analyzed texts from research articles of three countries (Korea, China, and Japan) through text-mining and co-occurrence analysis and compared the research subjects in each country. We extracted 199 words from 665 articles related to Artiodactyla of three countries through text-mining. Three word-clusters were formed as a result of co-occurrence analysis on extracted words. We determined that cluster1 was related to "habitat condition and ecology", cluster2 was related to "disease" and cluster3 was related to "conservation genetics and molecular ecology". The results of comparing the rates of occurrence of each word clusters in each country showed that they were relatively even in China and Japan whereas Korea had a prevailing rate (69%) of cluster2 related to "disease". In the regression analysis on the number of words per year in each cluster, the number of words in both China and Japan increased evenly by year in each cluster while the rate of increase of cluster2 was five times more than the other clusters in Korea. The results indicate that Korean researches on Artiodactyla tended to focus on diseases more than those in China and Japan, and few researchers considered other subjects including habitat characteristics, behavior and molecular ecology. In order to control the damage caused by Artiodactyla and to establish a reasonable policy for the protection of endangered species, it is necessary to accumulate basic ecological data by conducting researches on wild Artiodactyla more.