• 한국콘텐츠학회논문지
• /
• 제21권12호
• /
• pp.95-106
• /
• 2021

본 연구의 목적은 한국콘텐츠학회 논문지에 게재된 9,858건의 논문을 대상으로 토픽 모델링을 활용하여 지난 20년간 연구동향을 탐색함으로써 콘텐츠 연구개발에서의 주요 토픽을 도출하고 학술적 발전방향을 제공하는데 있다. 추출된 토픽의 신뢰성과 타당성을 확보하기 위해 양적 평가기법 뿐만 아니라 정성적 기법을 단계적으로 적용하여 연구자들이 합의한 수준의 말뭉치가 생성될 때까지 이를 반복적으로 수행하였으며 이에 따른 구체적인 분석 절차를 제시하였다. 분석 결과 8개의 핵심 토픽이 추출되었다. 이는 한국콘텐츠학회가 특정 학문 분야를 한정하지 않고 다양한 분야의 융·복합 연구 논문을 발간하고 있음을 보여준다. 또한 2012년 이전 상반기에는 공학기술 분야 토픽 비중이 상대적으로 높게 나타난 반면, 2012년 이후 하반기에는 사회과학 분야 토픽 출현 비중이 상대적으로 높게 나타났다. 구체적으로 '사회복지' 토픽은 상반기 대비 하반기에 약 4배수 증가세가 나타났다. 토픽별 추세분석을 통해 추세선의 변곡점이 나타난 특정 시점에 주목하여 해당 토픽의 연구동향에 영향을 미친 외적 변인을 탐색하였고 토픽과 외적 변인 간 관련성을 파악하였다. 본 연구결과가 국내 콘텐츠 관련 연구 개발 및 산업 분야에서 진행되고 있는 활발한 논의를 진행하는데 시사점을 제공할 수 있기를 기대한다.

• 아태비즈니스연구
• /
• 제12권3호
• /
• pp.51-69
• /
• 2021

Purpose - Based on literature studies of movie reviews and movie ratings, this study raised two research questions on the contents of online word of mouth and the number of movie screens as mediator variables. Research question 1 wanted to figure out which topics of word groups had a positive or negative impact on movie ratings. Research question 2 tried to identify the role of the number of movie screens between movie ratings and box office outcomes. Design/methodology/approach - Through R program, this study collected about 82,000 movie reviews and movie ratings posted on Naver's movie website to examine the role of online word of mouths and movie screen counts in 10 movies that were considered commercially unsuccessful with fewer than 2 million viewers despite securing about 1,000 movie screens. To confirm research question 1, topic modeling, a text mining technique, was conducted on movie reviews. In addition, this study linked the movie ratings posted on Naver with information of KOBIS by date, to identify the research question 2. Findings - Through topic modeling, 5 topics were identified. Topics found in this study were largely organized into two groups, the content of the movie (topic 1, 2, 3) and the evaluation of the movie (topics 4, 5). When analyzing the relationship between movie reviews and movie ratings with 5 mediators identified in topic modeling to probe research question 1, the topic word groups related to topic 2, 3 and 5 appeared having a negative effect on the netizen's movie ratings. In addition, by connecting two secondary data by date, analysis for research question 2 was implemented. The outcomes showed that the causal relationship between movie ratings and audience numbers was mediated by the number of movie screens. Research implications or Originality - The results suggested that the information presented in text format was harder to quantify than the information provided in scores, but if content information could be digitalized through text mining techniques, it could become variable and be analyzed to identify causality with other variables. The outcomes in research question 2 showed that movie ratings had a direct impact on the number of viewers, but also had indirect effects through changes in the number of movie screens. An interesting point is that the direct effect of movie ratings on the number of viewers is found in most American films released in Korea.

• 반도체디스플레이기술학회지
• /
• 제22권3호
• /
• pp.136-141
• /
• 2023

Artificial intelligence is becoming a global hot topic and is being actively applied in various industrial fields. Not only is artificial intelligence being applied to industrial sites in an on-premises method, but cloud-based artificial intelligence platforms are expanding into "as a service" type. The purpose of this study is to develop and verify a measurement tool for an evaluation framework for the adoption of a cloud-based artificial intelligence platform and test the interrelationships of evaluation variables. To achieve this purpose, empirical testing was conducted to verify the hypothesis using an expanded technology acceptance model, and factors affecting the intention to adopt a cloud-based artificial intelligence platform were analyzed. The results of this study are intended to increase user awareness of cloud-based artificial intelligence platforms and help various industries adopt them through the evaluation framework.

• Journal of Computing Science and Engineering
• /
• 제6권2호
• /
• pp.143-150
• /
• 2012

Computational techniques for topic classification can support qualitative research by automatically applying labels in preparation for qualitative analyses. This paper presents an evaluation of supervised learning techniques applied to one such use case, namely, that of labeling emotions, instructions and information in suicide notes. We train a collection of one-versus-all binary support vector machine classifiers, using cost-sensitive learning to deal with class imbalance. The features investigated range from a simple bag-of-words and n-grams over stems, to information drawn from syntactic dependency analysis and WordNet synonym sets. The experimental results are complemented by an analysis of systematic errors in both the output of our system and the gold-standard annotations.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
• /
• 한국정보과학회언어공학연구회 2021년도 제33회 한글 및 한국어 정보처리 학술대회
• /
• pp.287-292
• /
• 2021

좋은 자연어 이해 시스템은 인간과 같이 텍스트에서 단순히 단어나 문장의 형태를 인식하는 것 뿐만 아니라 실제로 그 글이 의미하는 바를 정확하게 추론할 수 있어야 한다. 이 논문에서 우리는 뉴스 헤드라인으로 뉴스의 토픽을 분류하는 open benchmark인 KLUE(Korean Language Understanding Evaluation)에 대하여 기존에 비교 실험이 진행되지 않은 시중에 공개된 다양한 한국어 라지스케일 모델들의 성능을 비교하고 결과에 대한 원인을 실증적으로 분석하려고 한다. KoBERT, KoBART, KoELECTRA, 그리고 KcELECTRA 총 네가지 베이스라인 모델들을 주어진 뉴스 헤드라인을 일곱가지 클래스로 분류하는 KLUE-TC benchmark에 대해 실험한 결과 KoBERT가 86.7 accuracy로 가장 좋은 성능을 보여주었다.

• 한국IT서비스학회지
• /
• 제17권2호
• /
• pp.191-205
• /
• 2018

With the advancement of artificial intelligence (AI) techniques, many consumer products have adopted AI features for providing proactive and personalized services to customers. One of the most prominent products featuring AI techniques is a smart speaker. The fundamental of smart speaker is a portable wireless Internet connecting speaker which already have existed in a consumer market. By applying AI techniques, smart speakers can recognize human voices and communicate with them. In addition, they can control other connecting devices and provide offline services. The goal of this study is to identify the impact of AI techniques for customer rating to the products. We compared customer reviews of other portable speakers without AI features and those of a smart speaker. Amazon echo is used for a smart speaker and JBL Flip 4 Bluetooth Speaker and Ultimate Ears BOOM 2 Panther Limited Edition are used for the comparison. These products are in the same price range ($50~100) and selected as featured products in Amazon.com. All reviews for the products were collected and common words for all products and unique words of the smart speaker were identified. Information gain values were calculated to identify the influences of words to be rated as positive or negative. Positive and negative words in all the products or in Amazon echo were identified, too. Topic modeling was applied to the customer reviews on Amazon echo and the importance of each topic were measured by summating information gain values of each topic. This study provides a way of identifying customer responses on the AI feature and measuring the importance of the feature among diverse features of the products.

• 인터넷정보학회논문지
• /
• 제19권4호
• /
• pp.27-33
• /
• 2018

최근 국내외 연구기관에서는 논문을 저널에 제출하는 과정에서 연구결과를 효과적으로 전달하기 위해 외부 기관을 통해 논문의 문맥, 전문 용어의 쓰임, 스타일 등에 대한 논문 교정을 진행하는 경우가 증가하고 있다. 하지만 대다수의 논문 교정 회사에서는 매니저의 주관적 판단에 따라 수동으로 논문 교정자를 할당하는 시스템이며, 이에 따라 논문의 주제에 대한 전문성이 부족한 교정자를 할당하여 논문 교정 의뢰인의 만족도가 떨어지는 사례가 발생하고 있다. 따라서 본 논문에서는 효과적인 논문 교정자 할당을 위해 논문의 토픽을 고려한 논문 교정자 매칭 방법론을 제안한다. Latent Dirichlet Allocation을 이용하여 문서의 토픽 모델링을 진행하고, 그 결과를 이용하여 코사인 유사도 기반으로 사용자간 유사도를 계산하였다. 특히, 논문 교정자의 토픽 모델링 과정에서, 대표 문서로 간주되는 문서의 중요도에 따라 가중치를 부여하여 빈도수에 차별을 둬 정밀한 토픽 추정을 가능하게 한다. 실제 서비스의 데이터를 이용한 실험에서 제안 방법론의 성능이 비교 방법론보다 우수함을 확인하였으며, 정성적 평가를 통해 논문 교정자 매칭 결과의 유효성을 검증하였다.

• 한국비블리아학회지
• /
• 제32권3호
• /
• pp.247-264
• /
• 2021

자살은 전 세계 사망 원인 중 4위이며 사회, 경제적 손실이 큰 난제이다. 본 연구는 자살 예방을 위하여 소셜미디어에 나타난 자살 관련 말뭉치를 구축하고 이를 통해 자살 경향 문헌을 분류할 수 있는 딥러닝 자동분류 모델을 만들고자 하였다. 또한, 자살 요인을 분석하기 위해 주제를 자동으로 추출하는 분석 기법인 토픽모델링을 활용하여 자살 관련 말뭉치를 세부 주제로 분류하고자 하였다. 이를 위해 소셜미디어 중 하나인 네이버 지식iN에 나타난 자살 관련 문헌 2,011개를 수집한 후 자살예방교육 매뉴얼을 기준으로 자살 경향 문헌 및 비경향 문헌 여부를 주석 처리하였으며, 이 데이터를 딥러닝 모델(LSTM, BERT, ELECTRA)로 학습시켜 자동분류 모델을 만들었다. 또한, 토픽모델링 기법의 하나인 LDA 기법으로 주제별 문헌을 분류하여 자살 요인을 발견하였고 이를 심층적으로 분석하기 위해 주제별로 동시출현 단어 분석 및 네트워크 시각화를 진행하였다.

• 농촌계획
• /
• 제24권4호
• /
• pp.69-80
• /
• 2018

In this study, we typified the project for revitalizing the rural area through text analysis using news data, and analyzed the main direction and characteristics of the project. In order to examine the factors emphasized among the issues related to the revitalization of rural areas, we used news data related to 'tourism' and 'livelihood', which are the main keyword of the project to promote rural areas. In the analysis, text mining techniques were used. Topic modeling was conducted on LDA techniques for major projects in 'tourism' and 'livelihood' keyword. Based on this, this study typified the projects that are carried out for the activation of rural areas by topic. As a result of the analysis, it was fount that the topics included in the project were distributed in 11 sub-types(Tourism Promotion, Regional Specialization, Local Festival, Development of Regional Scale, Urban and Rural Exchange, Agricultural Support, Community Forest Management, Improve the Settlement Environment, General Welfare Service, Low Class Support, Others). The characteristics of the rural revitalization projects were examined, and it was confirmed that domestic projects were carried out by tourism-oriented projects. To summarize, the government is making projects to revitalize rural areas through related ministries. Within the structure where the project is spreading to the region, a lot of projects are being carried out. It is understood that the tourism and welfare oriented projects are being carried out in the revitalization project of the domestic rural area. Therefore, in order to achieve the goal of rural revitalization, it is believed that it will be effective to carry out a balanced project to improve the settlement environment of the residents.

• The Korean Journal of Pain
• /
• 제34권1호
• /
• pp.82-93
• /
• 2021

Background: This study used bibliometric analysis of articles published about the topic of regional anesthesia from 1980-2019 with the aim of determining which countries, organizations, and authors were effective, engaged in international cooperation, and had the most cited articles and journals. Methods: All articles published from 1980-2019 included in the Web of Science database and found using the keywords regional anesthesia/anaesthesia, spinal anesthesia/anaesthesia, epidural anesthesia/anaesthesia, neuraxial anesthesia/anaesthesia, combined spinal-epidural, and peripheral nerve block in the title section had bibliometric analysis performed. Correlations between the number of publications from a country with gross domestic product (GDP), gross domestic product (at purchasing power parity) per capita (GDP PPP), and human development index (HDI) values were investigated with the Spearman correlation coefficient. The number of articles that will be published in the future was estimated with linear regression analysis. Results: Literature screening found 11,156 publications. Of these publications, 6,452 were articles. The top 4 countries producing articles were United States of America (n = 1,583), Germany (585), United Kingdom (510), and Turkey (386). There was a significant positive correlation found between the GDP, GDP PPP, and HDI markers for global countries with publication productivity (r = 0.644, P < 0.001; r = 0.623, P < 0.001, r = 0.542, P < 0.001). The most productive organizations were Harvard University and the University of Toronto. Conclusions: This comprehensive study presenting a holistic summary and evaluation of 6,452 articles about this topic may direct anesthesiologists, doctors, academics, and students interested in this topic.