• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.13-16
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• 2015

본 논문에서는 어휘의 동시 발생 (co-occurrence) 빈도와 분포를 이용한 회의록 요약방법을 제안한다. 회의록은 일반 문서와 달리 문서에 여러 세부적인 주제들이 나타나며, 잘못된 형식의 문장, 불필요한 잡담들을 포함하고 있기 때문에 이러한 특징들이 문서요약 과정에서 고려되어야 한다. 기존의 일반적인 문서요약 방법은 하나의 주제를 기반으로 문서 전체에서 가장 중요한 문장으로 요약하기 때문에 다중 주제 회의록 요약에는 적합하지 않다. 제안한 방법은 먼저 어휘의 동시 발생 (co-occurrence) 빈도를 이용하여 회의록 분할 (segmentation) 과정을 수행한다. 다음으로 주제의 구분에 따라 분할된 각 영역 (block)의 중요 단어 집합 생성, 중요 문장 추출 과정을 통해 회의록의 중요 문장들을 선별한다. 마지막으로 추출된 중요 문장들의 위치, 종속 관계를 고려하여 최종적으로 회의록을 요약한다. AMI meeting corpus를 대상으로 실험한 결과, 제안한 방법이 baseline 요약 방법들보다 요약 비율에 따른 평가 및 요약문의 세부 주제별 평가에서 우수한 요약 성능을 보임을 확인하였다.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.68-74
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• 2019

The purpose of this study was to identify research trends of 892 domestic articles (2009-2018) related to emotional labor by using text-mining and network analysis. To this end, the keyword of these papers were collected and coded and eventually converted to 871 nodes and 2625 links for network text analysis. First, network text analysis revealed that the top four main keyword, according to co-occurrence frequency, were burnout, turnover intention, job stress, and job satisfaction in order and that the frequency and the top four core keyword by degree centrality were all relatively the high. Second, based on the top four core keyword of degree centrality the ego network analysis was conducted and the keyword for connection centroid of each network were presented.

• Journal of Korean Library and Information Science Society
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• v.42 no.4
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• pp.353-374
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• 2011

Analyzing research paper published from 2005 to 2010, this study aims for analysing the research paradigm on multi-culture and understanding the structural characteristics of the multicultural knowledge via scientometric. Co-word network constructed by keywords in documents and their co-occurrence relationships is a kind of mapping knowledge structure. A total of 4,521 and 1,373 papers published between 2005 and 2010 were retrieved from the KRF Registered Journals and Proposed Journals. This paper employs k-core analysis method in the field of mapping knowledge structure to analyze keyword co-occurrence network of multicultural research in Korea. And Netminer 3 is employed to visualize the networks in this paper.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.117-120
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• 2001

In this work, we propose a new method of extracting and weighting representative keywords(RKs) from a few documents that might interest a user. In order to extract RKs, we first extract candidate terms and then choose a number of terms called initial representative keywords (IRKS) from them through fuzzy inference. Then, by expanding and reweighting IRKS using term co-occurrence similarity, the final RKs are obtained. Performance of our approach is heavily influenced by effectiveness of selection method of IRKS so that we choose fuzzy inference because it is more effective in handling the uncertainty inherent in selecting representative keywords of documents. The problem addressed in this paper can be viewed as the one of calculating center of document vectors. So, to show the usefulness of our approach, we compare with two famous methods - Rocchio and Widrow-Hoff - on a number of documents collections. The results show that our approach outperforms the other approaches.

• Asia pacific journal of information systems
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• v.20 no.4
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• pp.25-51
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• 2010

This study compares and contrasts the intellectual development of the MIS field in Korea from 2005 to 2009 to that of international trends by using a keyword co-occurrence network analysis of the two flagship journals: APJIS and MIS Quarterly. From 316 research articles in these two journals, 132 unique and most frequently co-occurred keywords were put into analysis. The results of structural equivalence show a mild correlation between APJIS and MIS Quarterly. The e-commerce, trust, and technology adoption are the high frequency keywords in both journals. In Korea e-learning, purchasing, and recommendation systems turn out to be important keywords while outsourcing, research method, quantitative method, design research, information theory, and empirical research are in average international journals. This connotes that the Korean scholarship tends to focus more on practically oriented topics, but the clustering and relational mapping of research topics in each journal show a mild level of overlap with distinctive orientations due to intrinsic disparities depending on the concerned journals' geographical scopes, namely domestic or global.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.53-77
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• 2012

This study analyses the difference of contents and tones of arguments among three Korean major newspapers, the Kyunghyang Shinmoon, the HanKyoreh, and the Dong-A Ilbo. It is commonly accepted that newspapers in Korea explicitly deliver their own tone of arguments when they talk about some sensitive issues and topics. It could be controversial if readers of newspapers read the news without being aware of the type of tones of arguments because the contents and the tones of arguments can affect readers easily. Thus it is very desirable to have a new tool that can inform the readers of what tone of argument a newspaper has. This study presents the results of clustering and classification techniques as part of text mining analysis. We focus on six main subjects such as Culture, Politics, International, Editorial-opinion, Eco-business and National issues in newspapers, and attempt to identify differences and similarities among the newspapers. The basic unit of text mining analysis is a paragraph of news articles. This study uses a keyword-network analysis tool and visualizes relationships among keywords to make it easier to see the differences. Newspaper articles were gathered from KINDS, the Korean integrated news database system. KINDS preserves news articles of the Kyunghyang Shinmun, the HanKyoreh and the Dong-A Ilbo and these are open to the public. This study used these three Korean major newspapers from KINDS. About 3,030 articles from 2008 to 2012 were used. International, national issues and politics sections were gathered with some specific issues. The International section was collected with the keyword of 'Nuclear weapon of North Korea.' The National issues section was collected with the keyword of '4-major-river.' The Politics section was collected with the keyword of 'Tonghap-Jinbo Dang.' All of the articles from April 2012 to May 2012 of Eco-business, Culture and Editorial-opinion sections were also collected. All of the collected data were handled and edited into paragraphs. We got rid of stop-words using the Lucene Korean Module. We calculated keyword co-occurrence counts from the paired co-occurrence list of keywords in a paragraph. We made a co-occurrence matrix from the list. Once the co-occurrence matrix was built, we used the Cosine coefficient matrix as input for PFNet(Pathfinder Network). In order to analyze these three newspapers and find out the significant keywords in each paper, we analyzed the list of 10 highest frequency keywords and keyword-networks of 20 highest ranking frequency keywords to closely examine the relationships and show the detailed network map among keywords. We used NodeXL software to visualize the PFNet. After drawing all the networks, we compared the results with the classification results. Classification was firstly handled to identify how the tone of argument of a newspaper is different from others. Then, to analyze tones of arguments, all the paragraphs were divided into two types of tones, Positive tone and Negative tone. To identify and classify all of the tones of paragraphs and articles we had collected, supervised learning technique was used. The Na$\ddot{i}$ve Bayesian classifier algorithm provided in the MALLET package was used to classify all the paragraphs in articles. After classification, Precision, Recall and F-value were used to evaluate the results of classification. Based on the results of this study, three subjects such as Culture, Eco-business and Politics showed some differences in contents and tones of arguments among these three newspapers. In addition, for the National issues, tones of arguments on 4-major-rivers project were different from each other. It seems three newspapers have their own specific tone of argument in those sections. And keyword-networks showed different shapes with each other in the same period in the same section. It means that frequently appeared keywords in articles are different and their contents are comprised with different keywords. And the Positive-Negative classification showed the possibility of classifying newspapers' tones of arguments compared to others. These results indicate that the approach in this study is promising to be extended as a new tool to identify the different tones of arguments of newspapers.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.699-714
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• 2021

Supercritical CO₂ (S-CO₂) Brayton cycle has been applied to various heat sources in recent decades, owing to the characteristics of compact structure and high efficiency. Understanding the research development in this emerging research field is crucial for future study. Thus, a bibliometric approach is employed to analyze the scientific publications of S-CO₂ cycle field from 2000 to 2019. In Scopus database, there were totally 724 publications from 1378 authors and 543 institutes, which were distributed over 55 countries. Based on the software-BibExcel, these publications were analyzed from various aspects, such as major research areas, affiliations and keyword occurrence frequency. Furthermore, parameters such as citations, hot articles were also employed to evaluate the research output of productive countries, institutes and authors. The analysis showed that each paper has been cited 13.39 times averagely. United States was identified as the leading country in S-CO₂ research followed by China and South Korea. Based on the contents of publications, existing researches on S-CO₂ are briefly reviewed from the five aspects, namely application, cycle configurations and modeling, CO₂-based mixtures, system components, and experiments. Future development is suggested to accelerate the commercialization of S-CO₂ power system.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.153-158
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• 2016

As the number of social network users increases, the information on event such as social issues and disasters receiving attention in each region is promptly posted by the bucket through social media site in real time, and its social ripple effect becomes huge. This study proposes a detection method of events that draw attention from users in specific region at specific time by using twitter data with regional information. In order to collect Twitter data, we use Twitter Streaming API. After collecting data, We implemented event detection system by analyze the frequency of a keyword which contained in a twit in a particular time and clustering the keywords that describes same event by exploiting keywords' co-occurrence graph. Finally, we evaluates the validity of our method through experiments.

• The Korean Journal of Food & Health Convergence
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• v.9 no.1
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• pp.19-28
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• 2023

The purpose of this study is to explore which areas have been more interested in depression research in Korea through analysis of academic papers related to depression, and then to provide insights that can solve future depression problems. 1,032 papers searched with the keyword "depression" in scienceON were analyzed using Python 3.7 for word frequency analysis, word co-occurrence analysis, BERTopic, LDA, and OLS regression analysis. The results of word frequency and co-occurrence frequency analysis showed that related words were composed around words such as patient, disorder and symptom. As a result of topic modeling, a total of 13 topics including 'childhood depression' and 'eating anxiety' were derived. And it has been identified as a topic of interest that 'suicidal thoughts', 'treatment', 'occupational health', and 'health treatment program' were statistically significant topics, while 'child depression' and 'female treatment' were relatively less. As a result of the analysis of research trends, future research will not only study physiological and psychological factors but also social and environmental causes, as well as it was suggested that various collaborative studies of experts in academia were needed such as convergence and complex perspectives for depression relief and treatment.

• The Journal of Economics, Marketing and Management
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• v.11 no.5
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• pp.45-55
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• 2023

Purpose: As one of the continuous studies on the offline distribution industry, the purpose of this study is to find ways for offline stores to respond to the growth of online shopping by identifying research trends on department stores. Research design, data and methodology: To this end, this study conducted word frequency analysis, word co-occurrence frequency analysis, BERTopic, LDA, and dynamic topic modeling using Python 3.7 on a total of 551 English abstracts searched with the keyword 'department store' in scienceON as of October 10, 2022. Results: The results of word frequency analysis and co-occurrence frequency analysis revealed that research related to department stores frequently focuses on factors such as customers, consumers, products, satisfaction, services, and quality. BERTopic and LDA analyses identified five topics, including 'store image,' with 'shopping information' showing relatively high interest, while 'sales systems' were observed to have relatively lower interest. Conclusions: Based on the results of this study, it was concluded that research related to department stores has so far been conducted in a limited scope, and it is insufficient to provide clues for department stores to secure competitiveness against online platforms. Therefore, it is suggested that additional research be conducted on topics such as the true role of department stores in the retail industry, consumer reinterpretation, customer value and lifetime value, department stores as future retail spaces, ethical management, and transparent ESG management.