• The Journal of Internal Korean Medicine
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• v.43 no.6
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• pp.1075-1088
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• 2022

Objectives: The aim of this study is to analyze cancer research trends in traditional Korean medical journals indexed in the Korea Citation Index since 2000. Methods: Cancer research papers published in traditional Korean medical journals were searched in databases from inception to October 2022. The numbers of publications by journal and by year were descriptively assessed. After natural language processing, topic modeling (based on Latent Dirichlet allocation) and keyword network analysis were conducted. Results: This research trend analysis involved 1,265 papers. Six topics were identified by topic modeling: case reports on symptom management, literature reviews, experiments on apoptosis, herbal extract treatments of breast carcinoma cell lines, anti-proliferative effects of herbal extracts, and anti-tumor effects. Keyword network analysis found that the effects of herbal medicine were assessed in clinical and experimental studies, while acupuncture was mainly mentioned in clinical reports. Conclusions: Cancer research papers in traditional Korean medical journals have contributed to evidence-based medicine. Further experimental studies are needed to elucidate the effects of on different hallmarks of cancer. Rigorous clinical studies are needed to support clinical guidelines.

• Journal of Korean Library and Information Science Society
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• v.53 no.3
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• pp.455-477
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• 2022

This study aimed to compare and analyze librarian teacher evaluation index from evaluation of teachers' competency development with the the topics of information utilization education. To this end, LDA topic modeling was conducted by collecting papers related to information utilization education published in four major journals in the field of literature and information from 1995 to May 2022. As a result of topic modeling, it can be seen that information utilization education (T10) was the most actively discussed at 12.0% of the 20 topics, followed by library utilization classes (T2) 10.4% and user service (T3) 8.8%.On the other hand, 3.3% of reading discussion (T7), 2.9% of reading education (T19), 2.1% of manpower management (T13), and 2.1% of librarian teacher job satisfaction (T17) showed the lowest distributions 3.3%, 2.9%, 2.1%, and 2.1%, respectively. In addition, although librarian teacher's class model development (T1) and curriculum development (T20) are essential processes for collaborative classes and information utilization education, they were not reflected in the current teacher competency development evaluation index. Therefore, this study proposed that 'instructional model and curriculum development' indicator should be added on 'training and support classes' factors in the Librarian Teacher Evaluation Index in Teachers' Competency Development Evaluation for further evaluation.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.81-103
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• 2022

It recognizes the importance of mental health and well-being worldwide and consistently records public happiness figures through the World Happiness Report. COVID-19, which occurred in China in 2019, has changed people's daily lives a lot. The accumulation of stress caused by the prolonged epidemic is affecting people's happiness. The present research has revealed negative mental health effects such as "depression" and "anxiety" after the pandemic. In this regard, it was revealed that the happiness index was also lowered numerically. It is insufficient to analyze specific issues about changes in the issue of happiness felt by the public in Korean society after the epidemic. Therefore, this study aims to identify changes in the happiness issue of Koreans after COVID-19 and find ways to improve happiness. Data were collected from various aspects by searching 32 sub keywords based on ERG theory by dividing the period before and after COVID-19. The results of topic modeling before and after COVID-19 were classified into seven areas of happiness index 2.0 published by the National Assembly Future Research Institute and compared and analyzed. Based on the results of comparing the results of the before and after topic from the perspective of each area, a plan to improve happiness was presented. The academic implications of this paper are that the research on psychological changes caused by COVID-19 was expanded by mining the opinions of the actual public on 'happiness'. In addition, it has practical implications in that it specifically presented measures to promote happiness by utilizing the area of objective happiness indicators based on the existing research on ways to reduce happiness promotion unhappiness.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.758-764
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• 2018

Digital documents such as patents, scholarly papers and research reports have author keywords which summarize the topics of documents. Different documents are likely to describe the same topic if they share the same keywords. Document clustering aims at clustering documents to similar topics with an unsupervised learning method. However, it is difficult to apply to a large amount of documents event though the document clustering is utilized to in various data analysis due to computational complexity. In this case, we can cluster and connect massive documents using keywords efficiently. Existing bottom-up hierarchical clustering requires huge computation and time complexity for clustering a large number of keywords. This paper proposes an inverted index based bottom-up clustering for keywords and analyzes the results of clustering with massive keywords extracted from scholarly papers and research reports.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.661-670
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• 2021

Research trends can be usefully used to determine the importance of research topics by period, identify insufficient research fields, and discover new fields. In this study, research trends of urban spaces, where various problems are occurring due to population concentration and urbanization, were analyzed by topic modeling. The analysis target was the abstracts of papers listed in the Korea Citation Index (KCI) published between 2002 and 2019. Topic modeling is an algorithm-based text mining technique that can discover a certain pattern in the entire content, and it is easy to cluster. In this study, the frequency of keywords, trends by year, topic derivation, cluster by topic, and trend by topic type were analyzed. Research in urban regeneration is increasing continuously, and it was analyzed as a field where detailed topics could be expanded in the future. Furthermore, urban regeneration is now becoming a regular research field. On the other hand, topics related to development/growth and energy/environment have entered a stagnation period. This study is meaningful because the correlation and trends between keywords were analyzed using topic modeling targeting all domestic urban studies.

• Journal of Information Technology Services
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• v.18 no.1
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• pp.153-171
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• 2019

Competition among cities has become fierce with decentralization and globalization, and each city tries to establish a brand image of the city to build its competitiveness and implement its policies based on it. At this time, surveys, expert interviews, etc. are commonly used to establish city brands. These methods are difficult to establish as sampling methods an empirical component, the biggest component of a city brand. In this paper, therefore, based on the precedent research's urban brand measurement and components, the words representing each city image property were extracted and relocated to five indicators to form the evaluation index. The constructed indicators have been validated through the review of three experts. Through the index, we analyzed the brands of four cities, Ulsan, Incheon, Yeosu, and Gyeongju, and identified the factors by using Topic Modeling and Word Cloud. This methodology is expected to reduce costs and monitor timely in identifying and analyzing urban brand images in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.7
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• pp.764-770
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• 2019

In this research, text mining techniques were used to analyze the papers related to the "4th Industry". In order to analyze the papers, total of 685 papers were collected by searching with the keyword "4th industry" in Korea Journal Index(KCI) from 2016 to 2019. We used Python-based web scraping program to collect papers and use topic modeling techniques based on LDA algorithm implemented in R language for data analysis. As a result of perplexity analysis on the collected papers, nine topics were determined optimally and nine representative topics of the collected papers were extracted using the Gibbs sampling method. As a result, it was confirmed that artificial intelligence, big data, Internet of things(IoT), digital, network and so on have emerged as the major technologies, and it was confirmed that research has been conducted on the changes due to the major technologies in various fields related to the 4th industry such as industry, government, education field, and job.

• The Journal of Information Systems
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• v.31 no.1
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• pp.289-304
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• 2022

Purpose The development of the network and mobile industries has induced companies to invest in information systems, leading a new industrial revolution. The Journal of Information Systems, which developed the information system field into a theoretical and practical study in the 1990s, retains a 30-year history of information systems. This study aims to identify academic values and research trends of JIS by analyzing the trends. Design/methodology/approach This study aims to analyze the trend of JIS by compounding various methods, named as TLS mining analysis. TLS mining analysis consists of a series of analysis including Term Frequency-Inverse Document Frequency (TF-IDF) weight model, Latent Dirichlet Allocation (LDA) topic modeling, and a text mining with Semantic Network Analysis. Firstly, keywords are extracted from the research data using the TF-IDF weight model, and after that, topic modeling is performed using the Latent Dirichlet Allocation (LDA) algorithm to identify issue keywords. Findings The current study used the summery service of the published research paper provided by Korea Citation Index to analyze JIS. 714 papers that were published from 2002 to 2012 were divided into two periods: 2002-2011 and 2012-2021. In the first period (2002-2011), the research trend in the information system field had focused on E-business strategies as most of the companies adopted online business models. In the second period (2012-2021), data-based information technology and new industrial revolution technologies such as artificial intelligence, SNS, and mobile had been the main research issues in the information system field. In addition, keywords for improving the JIS citation index were presented.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.145-153
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• 2020

In the rapidly changing era of the fourth industry, big data is being used in various fields. In recent years, the use of big data has been rapidly applied to overall cultural and artistic contents, and among them, the use of big data is essential as a film genre with a lot of capital. This research method is analyzed as the film , which won the Palme d'Or Prize of the 72nd Cannes Film Festival in 2019 and the works and directors' award at the Academy Awards. The analyzed value predicts the film's performance through opinion mining, which gives the value of the change and sensitivity of each data cycle, and extracts the utilization index and topic keywords of SNS such as Facebook and Twitter to reflect the audience's interest. Identify the factors. As such, if model performance and model development can be predicted through model analysis of film performance using big data, the efficiency of the film production process will be maximized while the risk of production cost and the risk of film failure will be minimized.

• Journal of the Korea Safety Management & Science
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• v.17 no.4
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• pp.1-12
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• 2015

Recent construction site large disaster occurs in, even normal disaster not be reduced, the efforts of pre-disaster prevention for this is also a need to study the evaluation index. By comprehensive examination zero reform the current lowest bid system has included the social responsibility index is scheduled, objective and quantitative evaluation indicators making construction safety areas that are included in the item of social responsibility is required ing. In this study, the construction, in order to prevent disasters, efforts pre disaster prevention be presented metrics in the construction safety in the field of comprehensive examination system and the evaluation index, it is intended to examine the evaluation items for the evaluation indices.