• 패션비즈니스
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• 제23권5호
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• pp.81-95
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• 2019

The purpose of this study is to research consumers' perception of the HiSeoul fashion show, which is being used by new designers as a means of promotion, and to propose a strategy for revitalizing new designer brands. This was done in order to secure basic data from fashion consumers, to help guide marketing strategies and promote rising designers. In this research, the consumers' perception of HiSeoul fashion show was verified using text-mining, data refinement and word clouding that was undertaken by TEXTOM3.0. Also, semantic network analysis, CONCOR analysis and visualization of the analysis results were performed using Ucinet 6.0 and NetDraw. "HiSeoul fashion show" was used as the keyword for text-mining and data was collected from March 1, 2018 to April 30, 2019. Using frequency analysis, TF-IDF, and N-gram, it was also shown that consumers are aware of places where shows are held, such as DDP and Igansumun. It was also revealed that consumers recognize rising designer brands, designer's names, the names of guests attending the show and the photo times. This study is meaningful in that it not only confirmed consumers' interest in new designer brands participating in the HiSeoul Fashion Show through big data but also confirmed that it is available as a marketing strategy to boost brand sales. This study suggests using HiSeoul show room to induce consumer sales, or inviting guests that match the brand image to promote them on SNS on the day the show is held for a marketing strategy.

• 패션비즈니스
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• 제23권3호
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• pp.85-100
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• 2019

This study examines changes in consumer perceptions of fashion shows, which are critical elements in the apparel industry and a means to represent a brand's image and originality. For this purpose, big data in clothing marketing, text mining, semantic network analysis techniques were applied. This study aims to verify the effectiveness and significance of fashion shows in an effort to give directions for their future utilization. The study was conducted in two major stages. First, data collection with the key word, "fashion shows," was conducted across websites, including Naver and Daum between 2015 and 2018. The data collection period was divided into the first- and second-half periods. Next, Textom 3.0 was utilized for data refinement, text mining, and word clouding. The Ucinet 6.0 and NetDraw, were used for semantic network analysis, degree centrality, CONCOR analysis and also visualization. The level of interest in "models" was found to be the highest among the perception factors related to fashion shows in both periods. In the first-half period, the consumer interests focused on detailed visual stimulants such as model and clothing while in the second-half period, perceptions changed as the value of designers and brands were increasingly recognized over time. The findings of this study can be utilized as a tool to evaluate fashion shows, the apparel industry sectors, and the marketing methods. Additionally, it can also be used as a theoretical framework for big data analysis and as a basis of strategies and research in industrial developments.

• International Journal of Internet, Broadcasting and Communication
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• 제15권3호
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• pp.211-218
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• 2023

Due to the implementation of COVID-19 distancing, interest and users in 'home training' are rapidly increasing. Therefore, the purpose of this study is to identify the perception of 'home training' through big data analysis on social media channels and provide basic data to related business sector. Social media channels collected big data from various news and social content provided on Naver and Google sites. Data for three years from March 22, 2020 were collected based on the time when COVID-19 distancing was implemented in Korea. The collected data included 4,000 Naver blogs, 2,673 news, 4,000 cafes, 3,989 knowledge IN, and 953 Google channel news. These data analyzed TF and TF-IDF through text mining, and through this, semantic network analysis was conducted on 70 keywords, big data analysis programs such as Textom and Ucinet were used for social big data analysis, and NetDraw was used for visualization. As a result of text mining analysis, 'home training' was found the most frequently in relation to TF with 4,045 times. The next order is 'exercise', 'Homt', 'house', 'apparatus', 'recommendation', and 'diet'. Regarding TF-IDF, the main keywords are 'exercise', 'apparatus', 'home', 'house', 'diet', 'recommendation', and 'mat'. Based on these results, 70 keywords with high frequency were extracted, and then semantic indicators and centrality analysis were conducted. Finally, through CONCOR analysis, it was clustered into 'purchase cluster', 'equipment cluster', 'diet cluster', and 'execute method cluster'. For the results of these four clusters, basic data on the 'home training' business sector were presented based on consumers' main perception of 'home training' and analysis of the meaning network.

• Nuclear Engineering and Technology
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• 제55권4호
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• pp.1410-1419
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• 2023

Public perception plays a crucial role in the successful completion of a nuclear power project. As a newcomer country to nuclear power, there are lots of misconceptions among the Bangladeshi people about nuclear energy. Consequently, it is crucial to minimize all the doubts among mass people and build up their positive outlook toward nuclear power. This demands a comprehensive survey to figure out the public opinion, concerns, false impressions, and knowledge gap regarding nuclear power. In the present study, these issues were addressed by a survey that was responded to by 661 persons for the 24 survey questions. The questions were categorized based on information, knowledge, faith, benefit, awareness, and technology. Feedback and responders' basic demographic and socioeconomic information were collected from various locations in Bangladesh through online and in-person surveys. The responses were analyzed in both statistical and descriptive ways. Some of the feedback was found to vary with age, sex, and education level while others were quite independent of these parameters. It is found that socioeconomic development and energy security can be achieved by the inclusion of nuclear energy in the power system master plan of the country. However, huge knowledge gaps and misconceptions were found among the public regarding nuclear energy. As per feedback, political instability and corruption may affect the national nuclear power project in Bangladesh. Low faith in the existing rules & regulations for nuclear power programs was also observed. The result of this study will be handy to develop the communication and public awareness strategy for a successful nuclear power project in Bangladesh.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.

• 대한교통학회지
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• 제8권1호
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• pp.55-71
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• 1990

The behavioral mechanism underlying the traffic assignment model is a choice, or decision-making process of traveling paths between origins and destinations. The deterministic approach to traffic assignment assumes that travelers choose shortest path from their origin-destination pair. Although this assumption seems reasonable, it presumes that all travelers have perfect information regarding travel time, that they make consistently correct decision, and that they all behave in identical fashion. Stochastic user equilibrium assignment relaxes these presumptions by including a random component in traveler's perception of travel time. The objective of this study is to compare "A Model of Deterministic User Equilibrium Assignment" with "Models of Stochastic User Equilibrium Assignment" in the theoretical and practical aspects. Specifically, SUE models are developed to logit and probit based models according to discrete choice functions. The models were applied to sioux Falls net ork consisting of 24 zones, 24 nodes and 76 links. The distribution of perceived travel time was obtained by using the relationship between speed and traffic flow.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.107.2-107
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• 2002

The objective of this study is to propose a lane changing and keeping method on a curved road for an automatic guidance of a vehicle. It is well known that the speed control of a vehicle in a curved road is essential in terms of vehicle stability and passenger safety because centrifugal force makes a vehicle to be on out of lane. And it is also natural to avoid the collision with other cars or obstructions with keeping the stability and drivability. The vehicle pose and the road curvature were calculated by geometrically fusing sensor data from camera image, tachometer and steering wheel encoder though the Perception Net in which not only the state variables, but also the corresponding uncer...

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2000년도 추계학술발표논문집 (상)
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• pp.473-476
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• 2000

최근 전자상거래에서 에이전트 기술들이 많이 나타나고 있는데, 주목해야 할 것은 패키지 형태로 내장될 수 있는 에이전트이다. 전자상거래 솔루션에 탑재되어 자동화시킨 에이전트로서 NetPerception 의 GroupLens 엔진과 MacroMedia의 LikeMinds가 있는데 이들은 협동적 필터링을 구현한 것들이다. 현재 이러한 협동적 필터링 에이전트 시스템이 탑재된 전자상거래 솔루션들이 등장하고 있다. 하지만 add-on 성격이 부족하고, 실제 협동적 필터링 알고리즘에 의해 고객의 취향이나 기호에 맞는 아이템을 추천하는 진정한 의미의 에이전트 시스템은 찾아보기 힘들다. 그래서, 이러한 점을 보완한 MindReader 시스템을 개발하였다. 제안된 알고리즘은 기존의 GroupLens 알고리즘에 클러스터링을 접목시킨 알고리즘을 사용하였다.

• 한국조경학회지
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• 제50권5호
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• pp.90-102
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• 2022

최근 힐링에 대한 관심이 증가함에 따라 힐링을 콘셉트로 하는 옥외 공간이 조성되고 있다. 보다 전문적이고 심층적인 옥외 힐링 장소 계획·설계·디자인을 위해 88,155건의 블로그 게시글 텍스트 데이터를 개체명 인식하여 텍스트 마이닝을 진행했다. 옥외 힐링 장소의 인식과 특징을 파악을 위해 출현 빈도 분석과 응집 분석을 진행하였다. 선행연구 고찰을 통해 힐링 장소의 6가지 요소를 도출하였으며, 시간과 인원을 추가한 총 8가지 요소를 통해 인식과 특성을 살펴보았다. 분석 결과 사람들은 힐링 장소를 방문하는 데 있어 장소적요소, 시간적요소, 사회적요소, 활동요소를 인원, 식물, 색상·형태, 심리적 요소보다 중요하게 생각하였다. 상위 출현 키워드를 통해 여러 가지 인식과 특성을 파악할 수 있었다. 응집 분석 결과를 통해 장소적요소, 시간적요소, 사회적요소의 키워드들이 응집되어 나타나 주로 어떤 장소, 어떤 시간대, 누구와 함께 방문하는지 구체적으로 살펴볼 수 있었다. 연구를 통해 실제 사람들이 작성한 인식 데이터를 대량 분석하여 힐링 장소의 인식과 특성을 도출하였으며, 계획과 마케팅적으로 활용할 수 있는 구체적인 요소가 나타남을 확인했다.

• 한국가정과교육학회지
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• 제32권3호
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• pp.179-197
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• 2020

본 연구는 언어 네트워크 분석방법을 활용하여 2000년부터 2019년까지 최근 20년간 KCI 등재 학술지에 게재된 가정과교육 논문의 연구 동향을 분석하였다. 총 501편의 가정과교육 논문을 대상으로, NetMiner 4.4를 활용하여 워드클라우드, 중심성 분석, 토픽모델링을 실시한 결과는 다음과 같다. 첫째, KCI 등재지에 게재된 가정과교육 논문의 수는 2000년대에 186편, 2010년대에 315편으로 점차 증가하는 추세이고, 가정과교육 논문이 게재된 학술지는 2000년대에 16종, 2010년대에 22종으로 더욱 다양해졌다. 전체 논문 수의 60%가 '한국가정과교육학회지'에 게재되었고, 2018년 이후 '학습자중심교과교육연구'에 게재된 논문이 급증한 것으로 나타났다. 둘째, 2000년대와 2010년대에 KCI 등재지에 게재된 가정과교육 연구의 주제는 교과 내용 분석, 수업 개발 및 적용, 교육과정 분석, 인식 조사 및 방향 탐색으로 범주화되었다. 2000년대에는 '가정과교사'가 주요 키워드로 등장하고, 인식 조사 및 방향 탐색 연구가 상대적으로 많이 이루어졌다. 2010년대에는 '개발' 키워드의 영향력이 커지고, 교과 내용 분석 및 수업을 개발하고 적용하는 연구가 상대적으로 많이 이루어진 것으로 나타났다. 본 연구는 분석 대상과 기간을 확대하여 가정과교육 연구 동향을 분석한 것에 의의가 있다.