• Smart Media Journal
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• v.11 no.11
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• pp.75-83
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• 2022

NIST in the United States has developed SCAP, a protocol that enables automated inspection and management of security vulnerability using existing standards such as CVE and CPE. SCAP operates by creating a checklist using the XCCDF and OVAL languages and running the prepared checklist with the SCAP tool such as the SCAP Workbench made by OpenSCAP to return the check result. SCAP checklist files for various operating systems are shared through the NCP community, and the checklist files include ID, title, description, and inspection method for each item. However, since the inspection items are simply listed in the order in which they are written, so it is necessary to classify and manage the items by type so that the security manager can systematically manage them using the SCAP checklist file. In this study, we propose a method of extracting the description of each inspection item from the SCAP checklist file written in OVAL language, classifying the categories through a machine learning model, and outputting the SCAP check results for each classified item.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.217-245
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• 2016

The purpose of this study is to verify how 7 sentiment domains extracted through sentiment analysis from social media have an influence on business performance. It consists of three phases. In phase I, we constructed the sentiment lexicon after crawling 45,447 pieces of VOC (Voice of the Customer) on 26 auto companies from the car community and extracting the POS information and built a seven-sensitive domains. In phase II, in order to retain the reliability of experimental data, we examined auto-correlation analysis and PCA. In phase III, we investigated how 7 domains impact on the market share of three major (GM, FCA, and VOLKSWAGEN) auto companies by using linear regression analysis. The findings from the auto-correlation analysis proved auto-correlation and the sequence of the sentiments, and the results from PCA reported the 7 sentiments connected with positivity, negativity and neutrality. As a result of linear regression analysis on model 1, we indentified that the sentimental factors have a significant influence on the actual market share. In particular, not only posotive and negative sentiment domains, but neutral sentiment had significantly impacted on auto market share. As we apply the availability of data to the market, and take advantage of auto-correlation of the market-related information and the sentiment, the findings will be a huge contribution to other researches on sentiment analysis as well as actual business performances in various ways.

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.239-262
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• 2021

The Korean Medical Journal (1930-1937) is the first Korean medical journal published by The Korean Medical Association, which Korean doctors established to resist Japanese medical organizations during the Japanese colonial period. Using the bibliometric research method for The Korean Medical Journal, this study aimed to analyze the journal as follows. First, the study analyzed the subject trends of medical research by extracting the MeSH terms from the title of the articles. Next, the study identified characteristics of authors, type of language used in the papers, publication year and countries of references included in the papers. Also, this study identified the researchers' interests by analyzing the frequency of keywords appearing in the roundtable titles. As a result of the research, infections, pathological symptoms and diseases of the digestive system were studied most often. Most authors belonged to Severance Union Medical College, and internal medicine and general surgery departments had the most authors. Most of the titles and texts of the papers were written in Korean and Chinese characters in combination. Of the 131 papers, only 40 contained abstracts, 22 of which were English abstracts, the most number. The study analyzed 1,103 references in the papers and found that the authors mainly cited the latest journals published in Japan, Germany, and the United States. The topics discussed the most in the roundtable talks were tuberculosis, neurasthenia, and gonorrhea in order. This research examined the history of the publication of The Korean medical journal. Also, it showed that Korean doctors accumulated their academic medical research results and contributed to improving medical conditions.

• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.101-119
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• 2020

The study aims to understand major topics and concerns of gender identity-related questions expressed by the users of the NAVER social Q&A site. To achieve this goal, we analyzed 2,120 questions created from 2010 to 2018 using natural language- and information retrieval-based methods. Results indicated that the major topics discussed by the users include interpersonal relationships, doubts about gender identity, sexual orientation, feelings and relationships, and concerns about gender identity. In addition, users mainly expressed concerns regarding general issues of gender identity; sexual orientation; negative cognition about gender identity; confession, coming-out, homosexuality; future, heterosexual relationships, military enlistment; and causes of gender identity confusion. The present study effectively derives information needs from real-world concerns about sexual identity by employing topic modeling techniques, and by comparing the advantages of exact match and tf-idf-based information retrieval methods extends methodology of Library and Information Science. Further, it has contributed to the academic maturity of the study of information behavior by observing the information needs or information-seeking behaviors of online community users with specific interests.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.179-200
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• 2019

Word-of-mouth (WoM) is defined by consumer activities that share information concerning consumption. WoM activities have long been recognized as important in corporate marketing processes and have received much attention, especially in the marketing field. Recently, according to the development of the Internet, the way in which people exchange information in online news and online communities has been expanded, and WoM is diversified in terms of word of mouth, score, rating, and liking. Social media makes online users easy access to information and online WoM is considered a key source of information. Although various studies on WoM have been preceded by this phenomenon, there is no meta-analysis study that comprehensively analyzes them. This study proposed a method to extract major researches by applying text mining techniques and to grasp the main issues of researches in order to find the trend of WoM research using scholarly big data. To this end, a total of 4389 documents were collected by the keyword 'Word-of-mouth' from 1941 to 2018 in Scopus (www.scopus.com), a citation database, and the data were refined through preprocessing such as English morphological analysis, stopwords removal, and noun extraction. To carry out this study, we adopted main path analysis (MPA) and word co-occurrence network analysis. MPA detects key researches and is used to track the development trajectory of academic field, and presents the research trend from a macro perspective. For this, we constructed a citation network based on the collected data. The node means a document and the link means a citation relation in citation network. We then detected the key-route main path by applying SPC (Search Path Count) weights. As a result, the main path composed of 30 documents extracted from a citation network. The main path was able to confirm the change of the academic area which was developing along with the change of the times reflecting the industrial change such as various industrial groups. The results of MPA revealed that WoM research was distinguished by five periods: (1) establishment of aspects and critical elements of WoM, (2) relationship analysis between WoM variables, (3) beginning of researches of online WoM, (4) relationship analysis between WoM and purchase, and (5) broadening of topics. It was found that changes within the industry was reflected in the results such as online development and social media. Very recent studies showed that the topics and approaches related WoM were being diversified to circumstantial changes. However, the results showed that even though WoM was used in diverse fields, the main stream of the researches of WoM from the start to the end, was related to marketing and figuring out the influential factors that proliferate WoM. By applying word co-occurrence network analysis, the research trend is presented from a microscopic point of view. Word co-occurrence network was constructed to analyze the relationship between keywords and social network analysis (SNA) was utilized. We divided the data into three periods to investigate the periodic changes and trends in discussion of WoM. SNA showed that Period 1 (1941~2008) consisted of clusters regarding relationship, source, and consumers. Period 2 (2009~2013) contained clusters of satisfaction, community, social networks, review, and internet. Clusters of period 3 (2014~2018) involved satisfaction, medium, review, and interview. The periodic changes of clusters showed transition from offline to online WoM. Media of WoM have become an important factor in spreading the words. This study conducted a quantitative meta-analysis based on scholarly big data regarding WoM. The main contribution of this study is that it provides a micro perspective on the research trend of WoM as well as the macro perspective. The limitation of this study is that the citation network constructed in this study is a network based on the direct citation relation of the collected documents for MPA.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.191-203
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• 2022

In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.

• Journal of Digital Convergence
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• v.10 no.2
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• pp.255-267
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• 2012

High Internet usage and the public's keen interest on health have influenced the health care system, and a potential value of the online health information and medical consultation market is immense. This study reveals results from data collected from Seoul residents in the age group of 20s in 2011. Out of 499 respondents, 75.2% answered that they used online health information; however, only 7.2% answered that they have used online medical consultation services. Findings on the purposes of using online medical consultation included treatments of symptoms(33.6%) and self-disciplines of one's health(19.5%). Mostly used Websites for health information search included search engines and blogs, but respondents preferred to use government sites and hospital sites in the future. When choosing a medical consultation, respondents preferred a certain website for different reasons including creditability of the consultant(23.7%), creditability of the organization(23.7%), rapid responses(21.2%), and more. Overall, although health information search via web is being highly utilized among people in their 20s, utilization of online medical consulting is not. Thus, promotion efforts to increase awareness and utilization of online medical consulting based on the site selection criteria, type of personal information disclosure, and other preferences are essential. Also, creating websites meeting these criteria is important.

• Journal of the Korean Society for information Management
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• v.37 no.1
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• pp.153-177
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• 2020

In the context of open science, data sharing and reuse are becoming important researchers' activities. Among the discussions about data sharing and reuse, data journals and data papers shows visible results. Data journals are published in many academic fields, and the number of papers is increasing. Unlike the data itself, data papers contain activities that cite and receive citations, thus creating their own intellectual structures. This study analyzed 14 data journals indexed by Web of Science, 6,086 data papers and 84,908 cited references to examine the intellectual structure of data journals and data papers in academic community. Along with the author's details, the co-citation analysis and bibliographic coupling analysis were visualized in network to identify the detailed subject areas. The results of the analysis show that the frequent authors, affiliated institutions, and countries are different from that of traditional journal papers. These results can be interpreted as mainly because the authors who can easily produce data publish data papers. In both co-citation and bibliographic analysis, analytical tools, databases, and genome composition were the main subtopic areas. The co-citation analysis resulted in nine clusters, with specific subject areas being water quality and climate. The bibliographic analysis consisted of a total of 27 components, and detailed subject areas such as ocean and atmosphere were identified in addition to water quality and climate. Notably, the subject areas of the social sciences have also emerged.

• Journal of the Korean Geographical Society
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• v.41 no.5 s.116
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• pp.582-599
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• 2006

Due to the growing popularity of mobile information technology, more people, especially in the general public, have access to computerized geospatial information systems for wayfinding tasks or urban navigation. One of the problems with the current services is that, whether the users are exploring or navigating, whether they are travelers who are totally new to a region or long-term residents who have a fair amount of regional knowledge, the same method is applied and the direction are given in the same way. However, spatial knowledge for a given urban region expands in proportion to residency. Urban navigation is highly dependent on cognitive mental images, which is developed through spatial experience and social communication. Thus, the wayfinding service for a regional community can be highly supported, using well-known regional places. This research is to develop the framework for urban navigation within a regional community. The concept of communal ontology is proposed to aid in urban regional navigation. The experimental work was implemented with case study to collect regional landmarks, develop the ontological model and represent it with formal structure. The final product of this study will provide the geographical information of a region to the other agent and be the fundamental information structure for cognitive urban regional navigation.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.121-125
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• 2007

물 수요예측을 실시함에 있어서 사회 경제의 장래동향과 도시의 특성 및 발전 동향을 반영하여 수행하여야 한다. 그러나 지금까지의 관행으로는 수도계획에서 사용할 수 있는 실사용량에 대한 조사와 통계가 이루어지지 않고 있다. 실제 현장에서 얻은 자료를 토대로 하여 수도계획 및 설계에 사용할 수 있는 신뢰성 있는 설계인자의 도출이 필요하다. 본 연구에서는 급수지역의 각 조사 가정의 물 사용량을 실측 조사하여 얻어진 자료를 토대로 하여 물 수요 구조의 변화를 파악할 수 있는 수단의 하나로 가정의 수돗물 사용특성과 경제적 요인에 따른 가정용수의 사용특성 경향을 파악하고자 하였다. 가정에서 사용된 용수량의 조건별 경향성을 분석하기 위하여 한국수자원공사에서 2002년부터 2006년까지 3년여에 걸쳐 표본 집단이 되는 전국 140개 가구에 유량계를 설치하여 유량 자료를 획득하였고, 설문조사를 실시하여 각 가정의 물 사용 특성인자들을 조사하였다. 이 자료를 대상으로 비교적 자료의 신뢰성을 높이기 위한 자료의 선별과정을 거쳤다. 이렇게 선별된 자료들을 경향성 분석에 쓰이는 Mann-Kendall test와 Spearman's Rho test를 이용하여 분석하였다. 그 결과를 바탕으로 가정 용수 소비패턴의 증가 감소에 영향을 끼치는 인자들을 추출하였다. 실측자료를 분석을 통하여 나타난 결과들을 바탕으로 용수 수요처의 조건별 특성을 분석하고, 이를 활용한 생활용수 예측모형을 개발함으로써 합리적인 수요예측에 의한 용수수요의 과다예측 우려를 해소하고, 경제적 수도시설계획을 수립하는 등 과학적 물 수요관리 정책 수립을 위한 의사결정도구가 제공될 수 있다.c}$C의 저온에서 저장한 감자는 $20^{\circ}$C에서 저장한 감자보다 발아의 지연과 함께 낮은 PGA증가율을 보였다.다 높았으며, 전반적인 선호도의 경우 G3(1.5%)를 가장 선호하는 것으로 나타났다. 백년초 분말 첨가 도토리묵의 경우 색상은 0.5% 첨가한 O1이 가장 높은 값을 나타냈으며, 외관은 1.5% 첨가한 O3가 가장 높은 값을 보였다. 향미와 신맛의 경우는 백년초 분말의 첨가량이 증가됨에 따라서 유의적으로 증가했다(p<0.001). 씹힘성, 탄력성, 견고성의 경우는 대조군이 가장 높았으며, 백년초 분말 첨가량이 증가함에 따라 유의적으로 낮아졌다(p<0.001), 떫은맛의 경우는 백년초 분말에 의한 신맛의 영향으로 1% 백년초 분말이 첨가된 O2 가장 높게 나타났다. 전반적인 선호도는 0.5% 백년초 분말이 첨가된 O1이 가장 높게 나타났다. 따라서 녹차와 백년초의 기능성을 살린 도토리묵을 실용화시키는 효과적인 배합비는 녹차 분말 1.5% 첨가와 백년초 분말 첨가 0.5%가 바람직한 것으로 보이며 백년초 분말은 1%까지도 가능한 것으로 나타났다. 그러므로 기능성 식품 소재로써 도토리묵에 녹차와 백년초 분말을 첨가하는 것은 충분히 활용할만한 가치가 있다고 사료된다.론적으로, 비육돈 사료 내 3.32%의 호맥 사일리지의 혼합급여는 혈액 내 코티졸 함량, 도체육의 명도와 황색도, 지방산 조성 및 영양소 소화율에 영향을 미치는 것으로 사료되나 이에 대한 보다 많은 연구가 필요할 것으로 판단된다.니티와 공원과의 관계로 공원 설계와 관리에 있어서 영국에서는 커뮤니티가 직접 고객(client)으로서 역