• Title/Summary/Keyword: Text Mining for Korean

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Analysis of the ordering factors influencing the awarding price ratio of service contract in KONEPS

  • Jung-Sung Ha;Tae-Hong Choi;Wan-Sup Cho
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.12
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    • pp.239-248
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    • 2023
  • The purpose of this study is to analyze the factors for service contracts that affect the successful bid price rate, focusing on the case of the country market. In the study, ordering organizations and bidders differentiated themselves from existing studies by analyzing service contracts that affect the successful bid price rate in a wide range of country markets. Comparative analysis of the awarding price ratio for services, this work provides a comparable result to the existing results in the previous literature. The analytical model used five independent variables such as budget, contract method, the days of the public notice, the awarding method, and the lowest awarding ratio. In the survey and analysis, big data was collected using text mining for service bids for Nara Market over the past 18 years and data was analyzed in a multi-dimensional way. The results of the analysis are as follows, (1) if budget does not determine the awarding price ratio. This is not the case in small amounts. (2) The contract method affects the awarding price ratio. (3) The days of the public notice increase, the awarding price ratio decrease. (4) the awarding method affects the awarding price ratio. (5) The lowest awarding ratio determines the awarding price ratio. Based on the results of empirical analysis, policy implications were sought.

Research Trends in Korean Healing Facilities and Healing Programs Using LDA Topic Modeling (LDA 토픽모델링을 활용한 국내 치유시설과 치유프로그램 연구 동향)

  • Lee, Ju-Hong;Lee, Kyung-Jin;Sung, Jung-Han
    • Journal of the Korean Institute of Landscape Architecture
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    • v.51 no.3
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    • pp.95-106
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    • 2023
  • Korean healing research has developed over the past 20 years along with the growing social interest in healing. The field of healing research is diverse and includes legislated natural-based healing. In this study, abstracts of 2,202 academic journals, master's, and doctoral dissertations published in KCI and RISS were collected and analyzed. As for the research method, LDA topic modeling used to classify research topics, and time-series publication trends were examined. As a result of the study, it identified that the topic of Korean healing research was connected with 5 types and 4 mediators. The five were "Healing Tourism," "Mind and Art Healing," "Forest Therapy," "Healing Space," and "Youth Restoration and Healing," and the four mediators were "Forest," "Nature," "Culture", and "Education". In addition, only legalized healing studies extracted from Korean healing research and the topics were analyzed. As a result, legalized healing research classified into four. The four types were "Healing Spatial Environment Plan", "Healing Therapy Experiment", "Agricultural Education Experiential Healing", and "Healing Tourism Factor". Forest Therapy, which has the largest amount of research in legalized healing, Agro Healing and Garden Healing which operate similar programs through plants, and Marine Healing using marine resources also analyzed. As a result, topics that show the unique characteristics of individual healing studies and topics that are considered universal in all healing studies derived. This study is significant in that it identified the overall trend of research on Korean healing facilities and programs by utilizing LDA topic modeling.

Pattern Analysis for Civil Complaints of Local Governments Using a Text Mining (텍스트마이닝에 의한 지자체 민원청구 패턴 분석)

  • Won, Tae Hong;Yoo, Hwan Hee
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.3
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    • pp.319-327
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    • 2016
  • Korea faces a wide range of problems in areas such as safety, environment, and traffic due to the rapid economic development and urbanization process. Despite the local governments’ efforts to deal with electronic civil complaints and solve urban problems, civil complaints have been on the increase year by year. In this study, we collected civil complaint data over the last six years from a small and medium-sized city, Jinju-si. In order to conduct a spatial distribution pattern analysis, we indicated the location data on the area through Geocoding after classifying the reasons for civil complaints and then extracted the location data of the civil complaint occurrence spots in order to analyze the correlation between electronic civil complaints and land use. Results demonstrated that electronic civil complaints in Jinju-si were clustered in residential, central commercial, and residential-industrial mixed-use areas—areas where land development had been completed within the city center. After analyzing the civil complaints according to the land use, results revealed that complaints about illegal parking were the highest. Regarding the analysis results of facility distribution within a 50m radius from the civil complaint areas, civil complaints occurred a lot in detached housing areas located within the commercial and residential-industrial mixed-use areas. In the case of residential areas(old downtown), civil complaints were condensed in the areas with many ordinary restaurants. This research explored civil complaints in terms of the urban space and can be expected to be effectively utilized in finding solutions to the civil complaints

A Study on the Contemporary Definition of 'GARDEN' - Keyword Analysis used Literature Research and Big Data - ('정원'의 시대적 정의에 관한 연구 - 문헌연구와 빅데이터를 활용한 키워드 분석을 중심으로-)

  • Woo, Kyungsook;Suh, Joo Hwan
    • Journal of the Korean Institute of Landscape Architecture
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    • v.44 no.5
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    • pp.1-11
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    • 2016
  • There has been an increasingly high interest in gardens and garden design in Korea recently. However, the usage of the term 'garden' is extremely varied and complex, and there has been very little academic research made on the meaning of garden. Therefore, this research attempts to investigate the ideas of current gardens and to elucidate their changing patterns by means of extensive literature research and big data analysis. The notion of garden in the past was broad including not only private space such as Madang(마당) and Teul(뜰), but also even field and grass land as public outdoor space. Yet, the meaning has become smaller to merely private space due to the change of dwelling systems due to high industrial development of the 20th century. Furthermore, the introduction of urban parks as an interactive space between nature and humans, the similar spatial function of gardens, has blurred the boundary between garden and park, which created confusion in understanding the concept of a garden. After all, garden is a subject for humans. The meanings of garden need to be recognized from various points of view since garden itself is a creation by the sum of diverse fields such as natural and social sciences as well as culturology. This discussion on the meaning of garden in the present day will give a conceptual foundation for future research on gardens and garden design. Also, the big data analysis employed here as a research method can help other similar research topics, particularly semantics in landscape architecture.

Assessment of Visual Landscape Image Analysis Method Using CNN Deep Learning - Focused on Healing Place - (CNN 딥러닝을 활용한 경관 이미지 분석 방법 평가 - 힐링장소를 대상으로 -)

  • Sung, Jung-Han;Lee, Kyung-Jin
    • Journal of the Korean Institute of Landscape Architecture
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    • v.51 no.3
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    • pp.166-178
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    • 2023
  • This study aims to introduce and assess CNN Deep Learning methods to analyze visual landscape images on social media with embedded user perceptions and experiences. This study analyzed visual landscape images by focusing on a healing place. For the study, seven adjectives related to healing were selected through text mining and consideration of previous studies. Subsequently, 50 evaluators were recruited to build a Deep Learning image. Evaluators were asked to collect three images most suitable for 'healing', 'healing landscape', and 'healing place' on portal sites. The collected images were refined and a data augmentation process was applied to build a CNN model. After that, 15,097 images of 'healing' and 'healing landscape' on portal sites were collected and classified to analyze the visual landscape of a healing place. As a result of the study, 'quiet' was the highest in the category except 'other' and 'indoor' with 2,093 (22%), followed by 'open', 'joyful', 'comfortable', 'clean', 'natural', and 'beautiful'. It was found through research that CNN Deep Learning is an analysis method that can derive results from visual landscape image analysis. It also suggested that it is one way to supplement the existing visual landscape analysis method, and suggests in-depth and diverse visual landscape analysis in the future by establishing a landscape image learning dataset.

The Characteristics and Improvement Directions of Regional Climate Change Adaptation Policies in accordance with Damage Cases (지자체 기후변화 적응 대책 특성 및 개선 방향)

  • Ahn, Yoonjung;Kang, Youngeun;Park, Chang Sug;Kim, Ho Gul
    • Journal of Environmental Impact Assessment
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    • v.25 no.4
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    • pp.296-306
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    • 2016
  • There is a growing interest in establishing a regional climate change adaptation policy as the climate change impact in the region and local scale increases. This study focused on the analysis of 32 regions on its characteristics of local climate change adaptation plans. First, statistic program R was used for conducting cluster analysis based on the frequency and budgets of adaptation plan. Further, we analyzed damage frequency from newspapers regarding climate change impacts in eight categories which were caused by extreme weather events on 2,565 cases for 24 years. Lastly, the characteristics of climate change adaptation plan was compared with damage frequency patterns for evaluating the adequacy of climate change adaptation plan on each cluster. Four different clusters were created by cluster analysis. Most clusters clearly have their own characteristics on certain sectors. There was a high frequency of damage in 'disaster' and 'health' sectors. Climate change adaptation plan and budget also invested a lot on those sectors. However, when comparing the relative rate among regional governments, there was a difference between types of damage and climate change adaptation plan. We assumed that the difference could come from that each region established their adaptation plans based on not only the frequency of damage, but vulnerability assessment, and expert opinions as well. The result of study could contribute to policy making of climate change adaptation plan.

A Study on the Research Trends for Smart City using Topic Modeling (토픽 모델링을 활용한 스마트시티 연구동향 분석)

  • Park, Keon Chul;Lee, Chi Hyung
    • Journal of Internet Computing and Services
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    • v.20 no.3
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    • pp.119-128
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    • 2019
  • This study aims to analyze the research trends on Smart City and to present implications to policy maker, industry professional, and researcher. Cities around globe have undergone the rapid progress in urbanization and the consequent dramatic increase in urban dwellings over the past few decades, and faced many urban problems in such areas as transportation, environment and housing. Cities around the globe are in a hurry to introduce Smart City to pursue a common goal of solving these urban problems and improving the quality of their lives. However, various conceptual approaches to smart city are causing uncertainty in setting policy goals and establishing direction for implementation. The study collected 11,527 papers titled "Smart City(cities)" from the Scopus DB and Springer DB, and then analyze research status, topic, trends based on abstracts and publication date(year) information using the LDA based Topic Modeling approaches. Research topics are classified into three categories(Services, Technologies, and User Perspective) and eight regarding topics. Out of eight topics, citizen-driven innovation is the most frequently referred. Additional topic network analysis reveals that data and privacy/security are the most prevailing topics affecting others. This study is expected to helps understand the trends of Smart City researches and predict the future researches.

The Perception Analysis of Autonomous Vehicles using Network Graph (네트워크 그래프를 활용한 자율주행차에 대한 인식 분석)

  • Hyo-gyeong Park;Yeon-hwi You;Sung-jung Yong;Seo-young Lee;Il-young Moon
    • Journal of Practical Engineering Education
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    • v.15 no.1
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    • pp.97-105
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    • 2023
  • Recently, with the development of artificial intelligence technology, many technologies for user convenience are being developed. Among them, interest in autonomous vehicles is increasing day by day. Currently, many automobile companies are aiming to commercialize autonomous vehicles. In order to lay the foundation for the government's new and reasonable policy establishment to support commercialization, we tried to analyze changes and perceptions of public opinion through news article data. Therefore, in this paper, 35,891 news article data mentioning terms similar to 'autonomous vehicles' over the past three years were collected and network analyzed. As a result of the analysis, major keywords such as 'autonomous driving', 'AI', 'future', 'Hyundai Motor', 'autonomous driving vehicle', 'automobile', 'industrial', and 'electric vehicle' were derived. In addition, the autonomous vehicle industry is developing into a faster and more diverse platform and service industry by converging with various industries such as semiconductor companies and big tech companies as well as automobile companies and is paying attention to the convergence of industries. To continuously confirm changes and perceptions in public opinion, it is necessary to analyze perceptions through continuous analysis of SNS data or technology trends.

Digital Archives of Cultural Archetype Contents: Its Problems and Direction (디지털 아카이브즈의 문제점과 방향 - 문화원형 콘텐츠를 중심으로 -)

  • Hahm, Han-Hee;Park, Soon-Cheol
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.17 no.2
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    • pp.23-42
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    • 2006
  • This is a study of the digital archives of Culturecontent.com where 'Cultural Archetype Contents' are currently in service. One of the major purposes of our study is to point out problems in the current system and eventually propose improvements to the digital archives. The government launched a four-year project for developing the cultural archetype content sources and establishing its related business with the hope of enhancing the nation's competitiveness. More specifically, the project focuses on the production of source materials of cultural archetype contents in the subjects of Korea's history. tradition, everyday life. arts and general geographical books. In addition, through this project, the government also intends to establish a proper distribution system of digitalized culture contents and to control copyright issues. This paper analyzes the digital archives system that stores the culture content data that have been produced from 2002 to 2005 and evaluates the current system's weaknesses and strengths. The summary of our findings is as follows. First. the digital archives system does not contain a semantic search engine and therefore its full function is 1agged. Second, similar data is not classified into the same categories but into the different ones, thereby confusing and inconveniencing users. Users who want to find source materials could be disappointed by the current distributive system. Our paper suggests a better system of digital archives with text mining technology which consists of five significant intelligent process-keyword searches, summarization, clustering, classification and topic tracking. Our paper endeavors to develop the best technical environment for preserving and using culture contents data. With the new digitalized upgraded settings, users of culture contents data will discover a world of new knowledge. The technology we introduce in this paper will lead to the highest achievable digital intelligence through a new framework.

Research Trends and Knowledge Structure of Digital Transformation in Fashion (패션 영역에서 디지털 전환 관련 연구동향 및 지식구조)

  • Choi, Yeong-Hyeon;Jeong, Jinha;Lee, Kyu-Hye
    • Journal of Digital Convergence
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    • v.19 no.3
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    • pp.319-329
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    • 2021
  • This study aims to investigate Korean fashion-related research trends and knowledge structures on digital transformation through information-based approaches. Accordingly, we first identified the current status of the relevant research in Korean academic literature by year and journal; subsequently, we derived key research topics through network analysis, and then analyzed major research trends and knowledge structures by time. From 2010 to 2020, we collected 159 studies published on Korean academic platforms, cleansed data through Python 3.7, and measured centrality and network implementation through NodeXL 1.0.1. The results are as follows: first, related research has been actively conducted since 2016, mainly concentrated in clothing and art areas. Second, the online platform, AR/VR, appeared as the most frequently mentioned topic, and consumer psychological analysis, marketing strategy suggestion, and case analysis were used as the main research methods. Through clustering, major research contents for each sub-major of clothing were derived. Third, major subject by period was considered, which has, over time, changed from consumer-centered research to strategy suggestion, and design development research of platforms or services. This study contributes to enhancing insight into the fashion field on digital transformation, and can be used as a basic research to design research on related topics.