• 품질경영학회지
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• 제51권4호
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• pp.701-713
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• 2023

Purpose: The primary purpose of this study is to integrate text mining and Quality Function Deployment (QFD) to automatically extract valuable information from customer reviews, thereby establishing a QFD frame- work to confirm genuine customer needs for New Product Development (NPD). Methods: Our approach combines text mining and QFD through topic modeling and sentiment analysis on a large data set of 56,873 customer reviews from Zappos.com, spanning five running shoe brands. This process objectively identifies customer requirements, establishes priorities, and assesses competitive strengths. Results: Through the analysis of customer reviews, the study successfully extracts customer requirements and translates customer experience insights and emotions into quantifiable indicators of competitiveness. Conclusion: The findings obtained from this research offer essential design guidance for new product develop- ment endeavors. Importantly, the significance of these results extends beyond the running shoe industry, presenting broad and promising applications across diverse sectors.

• 농촌계획
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• 제24권1호
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• pp.67-74
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• 2018

The rural areas are large residential space with fewer people than urban areas. That is why they are vulnerable to social services such as health care and security. This research analyzed the vulnerability of emergency relief service in rural village through text mining and the weighting value have been calculated. Based on the calculated statistics data, the police facilities are the most important, While the fire fighting and hospital facilities are important as well. In addition, the distance from the emergency relief service facility to the rural village was confirmed by using Open API. By combining these results, The vulnerable areas of the rural villages and the emergency relief service facilities were calculated and classified into 5 levels. For rural areas, the 1st class will have 33 places, following by 1,179 in 2nd class, 199 in 3rd class, 17 in 4th class and 8 in 5th class. Hence in order to further supplement the vulnerable areas to emergency relief service in villages, geographical relocation and policy approach of emergency relief service facilities are necessary.

• 인터넷정보학회논문지
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• 제19권1호
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• pp.155-166
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• 2018

These days, online media, such as blogospheres, online communities, and social networking sites, provides the uncountable user-generated content (UGC) to discover market intelligence and business insight with. The business has been interested in consumers, and constantly requires the approach to identify consumers' opinions and competitive advantage in the competing market. Analyzing consumers' opinion about oneself and rivals can help decision makers to gain in-depth and fine-grained understanding on the human and social behavioral dynamics underlying the competition. In order to accomplish the comparison study for rival products and companies, we attempted to do competitive analysis using text mining with online UGC for two popular and competing ramens, a market leader and a market follower, in the Korean instant noodle market. Furthermore, to overcome the lack of the Korean sentiment lexicon, we developed the domain specific sentiment dictionary of Korean texts. We gathered 19,386 pieces of blogs and forum messages, developed the Korean sentiment dictionary, and defined the taxonomy for categorization. In the context of our study, we employed sentiment analysis to present consumers' opinion and statistical analysis to demonstrate the differences between the competitors. Our results show that the sentiment portrayed by the text mining clearly differentiate the two rival noodles and convincingly confirm that one is a market leader and the other is a follower. In this regard, we expect this comparison can help business decision makers to understand rich in-depth competitive intelligence hidden in the social media.

• 한국정보시스템학회지:정보시스템연구
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• 제30권2호
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• pp.189-214
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• 2021

Purpose This paper aims to effectively utilize user-generated content (UGC) and analyze the market structure of a relatively new market which lacks rich user review information. Specifically, we propose a domain-specific text mining tool for the domestic craft beer market and visualize the market structure by incorporating how individual beer products are positioned in the perceptual map of consumers. Design/methodology/approach We collect user review information from Naver blogs, and extract words that describe beers. We identify semantic relationships between beer products through text mining, and then depending on these semantic relationships, construct a graph representing the market structure of the domestic craft beer market based on the consumer's perceptual map. Findings First, beer products produced in the same brewery are perceived as very similar to consumers. Second, only two products, 'Heukdang Milky Stout' and 'Gompyo', was noticeably distinguishable from other products. Third, even though 'Gyeongbokgung' is from a different brewery, it is located very close to the products of 'Jeju Beer' brewery such as 'Jeju Baeknokdam Ale' and 'Seongsan Ilchulbong Ale', which suggests the influence of 'landmark series.' We successfully show that our methodology effectively describes the market structure of the craft beer market.

• 한국의류산업학회지
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• 제24권5호
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• pp.545-556
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• 2022

To overcome the pandemic, a new strategy for innovation is in demand throughout the value chains of the fashion industry that emphasize the importance of fashion technology. Accordingly, as various viewpoints and fields of debate are unfolding to consider the direction of change led by fashion technology, it is necessary to make an active value judgment precedent by understanding the differences between various opinions. This study aims to derive keywords from fashion technology used during the pandemic, to infer the characteristics of each type of perspective and to understand their characteristics. For the research, this study combines text mining analysis and content analysis. Text mining analysis is used to find statistical patterns by collecting keywords from big data from online media, and content analysis is used to interpret the data qualitatively. After analyzing the results of this study, the following observations are made. First, the perspective of positive acceptance seeks to maximize the perception and sensory action of fashion through technology; this amplifies experience, an opportunity for innovation and efficiency. Second, critical vigilance highlights the side effects of radical changes in fashion technology, characterized by concerns about capital-centered polarization, threats to human rights, and infringement of creative thinking. Lastly, the perspective of gradual adoption is the gradual convergence of technologies, characterized by the pursuit of an appropriate balance.

• 한국콘텐츠학회논문지
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• 제11권10호
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• pp.59-68
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• 2011

축구 경기를 분석하고 이를 팀 전략 수립에 활용하는 축구 분석관의 역할이 강조됨에 따라, 방송용 축구 경기에서 주요 이벤트의 탐지와 같은 절차적 기능 이상의 고수준의 해석 방법들이 요구되고 있다. 본 논문에서는 인터넷 기반의 텍스트 방송인 축구 웹 캐스트에서 실시간으로 제공하는 텍스트 정보를 기반으로 텍스트 마이닝을 이용한 축구 경기의 전략 수립이 가능한 고수준의 해석 기법을 제안한다. 제안하는 해석기법은 축구 웹 캐스트의 텍스트 정보와 도메인 지식을 기반으로 축구 경기의 다양한 속성, 동작 그리고 이벤트 등 메타데이터를 추출하고, 인덱싱하고, 텍스트 마이닝의 다양한 해석 기법인 연관 규칙 마이닝, 성장도 분석, 그리고 패스파인더 네트워크 분석 기법 등을 사용함으로써 유용한 지식을 추출한다. 실제 2010년 월드컵의 스페인 팀 경기들을 중계한 웹 캐스트의 텍스트 정보를 대상으로 제안된 기법의 타당성을 실험적으로 검증한다.

• 인터넷정보학회논문지
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• 제16권4호
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• pp.71-81
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• 2015

With the increasing influence of online media, company websites have become important communication channels between companies and customers. Companies use their websites as a marketing tool for a variety of purposes, including enhancing their image and selling products or services. Many researchers have examined the criteria, methods, and tools for website evaluation, but most have focused on usability. Prior content analyses have focused not on text content but on website components, an approach likely to produce subjective evaluations. This study attempts to objectively evaluate company websites by utilizing text mining. We analyze the usefulness of company websites by presenting visualized outputs from a business perspective, allowing practitioners to easily understand the results of the website evaluation and use them in decision making. To demonstrate our method empirically, we selected a company with a number of affiliates in Korea and analyzed the text content of their websites to assess their usefulness using natural language processing and graphics packages in R. Practitioners can easily employ our objective evaluation method, and researchers can use it to gain a new perspective on website evaluation.

• 한국BIM학회 논문집
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• 제13권3호
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• pp.39-47
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• 2023

This study aims to introduce a model for enhancing community well-being through the utilization of public open data. To objectively assess abstract notions of residential satisfaction, text data from complaints is analyzed. By leveraging accessible public data, costs related to data collection are minimized. Initially, relevant text data containing civic complaints is collected and refined by removing extraneous information. This processed data is then combined with meaningful datasets and subjected to topic modeling, a text mining technique. The insights derived are visualized using Geographic Information System (GIS) and Application Programming Interface (API) data. The efficacy of this analytical model was demonstrated in the Godeok/Gangil area. The proposed methodology allows for comprehensive analysis across time, space, and categories. This flexible approach involves incorporating specific public open data as needed, all within the overarching framework.

• BMB Reports
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• 제56권11호
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• pp.594-599
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• 2023

A number of therapeutic drugs have been developed from functional chemicals found in plants. Knowledge of plants used for medicinal purposes has historically been transmitted by word of mouth or through literature. The aim of the present study is to provide a systemic platform for the development of lead compounds against breast cancer based on a traditional medical text. To verify our systematic approach, integrating processes consisted of text mining of traditional medical texts, 3-D virtual docking screening, and in vitro and in vivo experimental validations were demonstrated. Our text analysis system identified rutin as a specific phytochemical traditionally used for cancer treatment. 3-D virtual screening predicted that rutin could block EGFR signaling. Thus, we validated significant anti-cancer effects of rutin against breast cancer cells through blockade of EGFR signaling pathway in vitro. We also demonstrated in vivo anti-cancer effects of rutin using the breast cancer recurrence in vivo models. In summary, our innovative approach might be proper for discovering new phytochemical lead compounds designing for blockade of malignant neoplasm including breast cancer.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권12호
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• pp.4467-4488
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• 2014

The bibliometric analysis is widely used for understanding research domains, trends, and knowledge structures in a particular field. The analysis has majorly been used in the field of information science, and it is currently applied to other academic fields. This paper describes the analysis of academic literatures for classifying research domains and for suggesting empty research areas in the telecommunications policy. The application software is developed for retrieving Thomson Reuters' Web of Knowledge (WoK) data via web services. It also used for conducting text mining analysis from contents and citations of publications. We used three text mining techniques: the Keyword Extraction Algorithm (KEA) analysis, the co-occurrence analysis, and the citation analysis. Also, R software is used for visualizing the term frequencies and the co-occurrence network among publications. We found that policies related to social communication services, the distribution of telecommunications infrastructures, and more practical and data-driven analysis researches are conducted in a recent decade. The citation analysis results presented that the publications are generally received citations, but most of them did not receive high citations in the telecommunications policy. However, although recent publications did not receive high citations, the productivity of papers in terms of citations was increased in recent ten years compared to the researches before 2004. Also, the distribution methods of infrastructures, and the inequity and gap appeared as topics in important references. We proposed the necessity of new research domains since the analysis results implies that the decrease of political approaches for technical problems is an issue in past researches. Also, insufficient researches on policies for new technologies exist in the field of telecommunications. This research is significant in regard to the first bibliometric analysis with abstracts and citation data in telecommunications as well as the development of software which has functions of web services and text mining techniques. Further research will be conducted with Big Data techniques and more text mining techniques.