• The Journal of the Korea Contents Association
• /
• v.13 no.4
• /
• pp.427-439
• /
• 2013

With the fast development of complex science, lots of social networks are studied. We know that the social network is widely applied in analyzing issues in human culture, economics and web sciences. Recently we witness that some researchers began to compare the social network constructed from fiction literatures(literature social network) and the real social network obtained from practice. But we point that previous approaches for literature social network have some drawbacks since they completely depend on the biographical dictionary constructed for a designated literature. So since the previous approach focus on the few important characters and peoples around them, we can not understand the global structure of all characters appeared in the literature at least once. We propose one method to extract all characters appeared in the literature and how to make the social network from that information. Also we newly propose K-critical network by applying frequency of the named characters and the strength of relationship among all textual characters. Our experiment shows that the K-critical measure could be one crucial quantitative measure to compute the relationship strength among characters appeared in the object literature.

• Journal of Digital Convergence
• /
• v.14 no.12
• /
• pp.237-243
• /
• 2016

Since realtime search keywords of portal sites are arranged in descending order by instant increasing rates of search numbers, they easily show issues increasing in interests for a short time. But they have the limits extracted different results by portal sites and not shown issues by a period. Thus, to find key issues from the whole realtime search keywords for certain period, and to show results of summarizing them and analyzing differences, is significant in providing the basis of understanding issues more practically and in maintaining consistency of them. This paper analyzes differences of week key issues extracted from week analysis of realtime search keywords provided by two typical portal sites. The results of experiments show that the portal group means of realtime search keywords by the independent t-test and the survival functions of realtime search keywords by the survival analysis are statistically significant differences.

• Journal of Digital Convergence
• /
• v.18 no.9
• /
• pp.17-27
• /
• 2020

News articles and blog posts have influence on social agenda setting and this study applied text mining on the subject of solar PV in rural area appeared in those media. Texts are gained from online news articles and blog posts with rural solar PV as a keyword by web scrapping, and these are analysed by sentiment analysis and topic modeling technique. Sentiment analysis shows that the proportion of negative texts are significantly lower in blog posts compared to news articles. Result of topic modeling shows that topics related to government policy have the largest loading in positive articles whereas various topics are relatively evenly distributed in negative articles. For blog posts, topics related to rural area installation and environmental damage are have the largest loading in positive and negative texts, respectively. This research reveals issues related to rural solar PV by combining sentiment analysis and topic modeling that were separately applied in previous studies.

• Journal of Digital Convergence
• /
• v.15 no.2
• /
• pp.527-535
• /
• 2017

As interest increases in health promotion through sports, demand for public sports facilities is steadily growing. However, there is a lack of research on operation and management compared with the supply plan of public sports facility. In this context, the aim of this study is to address problems of management of public sports centers and suggest strategies for vitalizing the facilities through the big-data. The data are collected from web such as news, blog, and cafe for one year in 2015. From the big-data, We can find that the national sports centers and the open gyms showed similar users' behavior but showed different needs. Both facilities have been used as sports and leisure area and have a high percentage of visitors for other purposes such as walking, picnics, etc. However, while the national sports facilities which were used for more specialized programs, the open sports center were used as leisure space.

• Archives of design research
• /
• v.15 no.3
• /
• pp.271-280
• /
• 2002

These days information technology and internet have made startling progress. In these developing environments, the strategy or marketing based on existing off-line is getting more difficult to accomplish the role of the improvement of business competitive power, and they are bringing out a lot of changes in information management and marketing performance method about consumers due to digital networking between companies and consumers. These developments and changes make many varieties in the way of design studying methodology. Therefore, in this study, considering the aspects of design, society and environment, after I developed the consumer response framework about products design which is argued by Bloch(1995) ; distinct relationship model among preference degree- design image adjective - design factors, we established design information abstraction solution combined with the interaction based on IT as eCRM in real time. This suggested solutions will provide product designers with good information in finding the design factors which consumers prefer.

• Korean Journal of Oriental Medicine
• /
• v.17 no.3
• /
• pp.77-85
• /
• 2011

Objectives : The purpose of this study was to develop a simulator which can analyze the anti-inflammatory effects of medical herbs based on e-cell concerning p38 MAPK signal pathway. Methods : We collected data concerning medical herbs with anti-inflammatory effects and the active compounds to provide as a fundamental databse and to validate the newly developed algorithm. At this time, we used the target database as pubmed and gathered the data by data mining tool, pathway studio. Also we have developed the web-based search system for confirming database related to anti-inflammation. We researched the mechanism of actions of proteins in p38 MAPK signal pathway when active compound has been inserted into the network. We reduced total network into TAK-MKK3-p38 and made the two types of mathematical model about active compounds' interaction. Results & Conclusion : We constructed the database which have 69 cases of medical herbs, 71 cases of active compounds, about 8,000 cases of URL(Uniform Resource Locator) related to papers and reports. We designed the ordinary differential equations for response of TAK, MKK3, p38 in e-cell's cytosol and nucleus. We used this formular as measure whether an active compound of medicinal plants which is inputted by an user would have an anti-inflammation effects. We developed the visualization program which could show the change of concentration over time.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.9 no.1
• /
• pp.387-394
• /
• 2019

Recently, the importance of big data has been increased, and demand for data analysis for the big data is also increased. R language is developed for data analysis, and users are analyzing data by using algorithms of various statistics, machine learning and data mining packages in R language. However, it is difficult to develop an application using R. Early study proposed a method to call R script through another language such as PHP, Java, and so on. However, it is troublesome to write such a development method in addition to R in combination with other languages. In this study, we introduce how to write API using only R language without using another language by using Plumber package. We also propose a solution for security issues related with R API. If we use propose technology for developing web application, we can expect high productivity, easy of use, and easy of maintenance.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.4
• /
• pp.357-364
• /
• 2019

As industrial information disclosure by insider's rate is around 80%, most of relevant researches explain briefly its causes are discontent of salary or human resources system. This paper scrapes texts on Jobplanet, an anonymous company review website and analyzes discontent keyword by 7 related area and their contexts to find out more details on brief causes referred above. After drawing LGG (Local Grammar Graph) by each areas with related dictionary list, this paper shows an example of concordance as a proof and several ways for human resources leakage prevention. Finally, text analysis results are compared with previous researches based on survey with limited questions and answers. This study is meaningful to expand the scope of employee discontent analysis with company review text and provide more specific, granular and honest discontent vocabularies.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.9
• /
• pp.13-25
• /
• 2021

In the age of digital innovation based on the Internet, Information and Communication and Artificial Intelligence technologies, huge amounts of datasets are being generated, collected, accumulated, and opened on the web by various public institutions providing useful and public information. In order to analyse, gain useful insights and information from data, Formal Concept Analysis(FCA) has been successfully used for analyzing, classifying, clustering and visualizing data based on the binary relation between objects and attributes in the dataset. In this paper, we present an approach for enhancing the analysis of relational attributes of data within the extended framework of FCA, which is designed to classify, conceptualize and visualize sets of objects described not only by attributes but also by relations between these objects. By using the proposed tool, RCA wizard, several experiments carried out on some public open datasets demonstrate the validity and usability of our approach on generating and visualizing conceptual hierarchies for extracting more useful knowledge from datasets. The proposed approach can be used as an useful tool for effective data analysis, classifying, clustering, visualization and exploration.

• The Journal of Korean Academic Society of Nursing Education
• /
• v.27 no.2
• /
• pp.175-185
• /
• 2021

Purpose: The aim of this study was to identify core keywords and topic groups in the 'Gestational diabetes mellitus (GDM) and Breastfeeding' field of research for better understanding research trends in the past 20 years. Methods: This was a text-mining and topic modeling study composed of four steps: 1) collecting abstracts, 2) extracting and cleaning semantic morphemes, 3) building a co-occurrence matrix, and 4) analyzing network features and clustering topic groups. Results: A total of 635 papers published between 2001 and 2020 were found in databases (Web of Science, CINAHL, RISS, DBPIA, RISS, KISS). Among them, 3,639 words extracted from 366 articles selected according to the conditions were analyzed by text network analysis and topic modeling. The most important keywords were 'exposure', 'fetus', 'hypoglycemia', 'prevention' and 'program'. Six topic groups were identified through topic modeling. The main topics of the study were 'cardiovascular disease' and 'obesity'. Through the topic modeling analysis, six themes were derived: 'cardiovascular disease', 'obesity', 'complication prevention strategy', 'support of breastfeeding', 'educational program' and 'management of GDM'. Conclusion: This study showed that over the past 20 years many studies have been conducted on complications such as cardiovascular diseases and obesity related to gestational diabetes and breastfeeding. In order to prevent complications of gestational diabetes and promote breastfeeding, various nursing interventions, including gestational diabetes management and educational programs for GDM pregnancies, should be developed in nursing fields.