• Title/Summary/Keyword: 키워드 가치 평가

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A Study on the Gamification Technology Valuation Framework (게이미피케이션 기술 가치 평가 프레임워크 연구)

  • Baek, Junho;Jang, Jintae;Jeong, Jiyong;Kim, Sangkyun
    • Journal of Korea Game Society
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    • v.18 no.3
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    • pp.17-26
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    • 2018
  • As the concept of experience economy has been accelerated recently, user experience is more emphasized today, most of all. And related representative keywords are gamification. Gamification characterized by that intangible elements are produced and consumed through various interactions between providers and users and by having a structure that is difficult to generalize and objectify to economic value. Therefore, the purpose of the present study is to develop a quantitative valuation indicator of concept and standardize the valuation formula covering economic value for gamification technology and overall framework from the perspective of evaluating economic values of intangible technologies such as of knowledge, design, contents, and service of a company.

Recent Ecological Asset Research Trends using Keyword Network Analysis (키워드 네트워크 분석을 활용한 생태자산 연구 경향 분석)

  • Kim, Byeori;Lee, Jae-Hyuck;Kwon, Hyuksoo
    • Journal of Environmental Impact Assessment
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    • v.26 no.5
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    • pp.303-314
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    • 2017
  • The purpose of this study was to determine domestic and foreign ecological asset research trends. We aimed to understand ecological assets research directions and trends by comprehensively analyzing 12 keywords, including those similar to keywords for comparable assets, to identify related fields and regions. Extensive analysis of domestic and foreign studies was conducted through keyword network analysis of textural information. This approach is helpful for understanding the flow of information and identifying research directions. Foreign studies based on sustainability were connected with 'Economic assessment', 'Management' and 'Policy' areas. It was difficult to determine domestic research trends because there are fewer domestic studies than foreign. There were studies that sought to identify economic value of developing regions. This research can be used to guide the research direction for future ecosystem asset analysis in Korea.

A Study on Keywords Extraction from Entertainment News using Bigdata Processing (빅데이터 처리를 통한 연예 뉴스에서의 키워드 추출에 관한 연구)

  • Yoo, Sang-Hyun;Lee, Sang-Jun
    • Jounal of The Korea Society of Information Technology Policy & Management
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    • v.11 no.6
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    • pp.1503-1507
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    • 2019
  • With the softness of online entertainment news articles and the increasing number of quick-reporting articles in the entertainment sector, many people have access to entertainment front-page articles and are now able to make reviews of celebrities. It is not easy to systematically analyze which news articles are about which celebrities in a real-time environment, although their reputation is a key factor in the entertainment agency's business strategy, which should make the most of its affiliated celebrity resources. Based on the amount of celebrity references mentioned in entertainment news data, this paper proposes an entertainment news keyword analysis system, which extracts celebrities that are the subject of the article and associates them with the celebrity entertainment agency in question. Through the system proposed in this paper, advertisers or entertainment agencies can judge the value of the celebrity as reference material for the business. In addition, it can lay the groundwork for an investment strategy by predicting the outlook for the entertainment company for brokerages and investors.

A Methodology for Extracting Shopping-Related Keywords by Analyzing Internet Navigation Patterns (인터넷 검색기록 분석을 통한 쇼핑의도 포함 키워드 자동 추출 기법)

  • Kim, Mingyu;Kim, Namgyu;Jung, Inhwan
    • Journal of Intelligence and Information Systems
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    • v.20 no.2
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    • pp.123-136
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    • 2014
  • Recently, online shopping has further developed as the use of the Internet and a variety of smart mobile devices becomes more prevalent. The increase in the scale of such shopping has led to the creation of many Internet shopping malls. Consequently, there is a tendency for increasingly fierce competition among online retailers, and as a result, many Internet shopping malls are making significant attempts to attract online users to their sites. One such attempt is keyword marketing, whereby a retail site pays a fee to expose its link to potential customers when they insert a specific keyword on an Internet portal site. The price related to each keyword is generally estimated by the keyword's frequency of appearance. However, it is widely accepted that the price of keywords cannot be based solely on their frequency because many keywords may appear frequently but have little relationship to shopping. This implies that it is unreasonable for an online shopping mall to spend a great deal on some keywords simply because people frequently use them. Therefore, from the perspective of shopping malls, a specialized process is required to extract meaningful keywords. Further, the demand for automating this extraction process is increasing because of the drive to improve online sales performance. In this study, we propose a methodology that can automatically extract only shopping-related keywords from the entire set of search keywords used on portal sites. We define a shopping-related keyword as a keyword that is used directly before shopping behaviors. In other words, only search keywords that direct the search results page to shopping-related pages are extracted from among the entire set of search keywords. A comparison is then made between the extracted keywords' rankings and the rankings of the entire set of search keywords. Two types of data are used in our study's experiment: web browsing history from July 1, 2012 to June 30, 2013, and site information. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The original sample dataset contains 150 million transaction logs. First, portal sites are selected, and search keywords in those sites are extracted. Search keywords can be easily extracted by simple parsing. The extracted keywords are ranked according to their frequency. The experiment uses approximately 3.9 million search results from Korea's largest search portal site. As a result, a total of 344,822 search keywords were extracted. Next, by using web browsing history and site information, the shopping-related keywords were taken from the entire set of search keywords. As a result, we obtained 4,709 shopping-related keywords. For performance evaluation, we compared the hit ratios of all the search keywords with the shopping-related keywords. To achieve this, we extracted 80,298 search keywords from several Internet shopping malls and then chose the top 1,000 keywords as a set of true shopping keywords. We measured precision, recall, and F-scores of the entire amount of keywords and the shopping-related keywords. The F-Score was formulated by calculating the harmonic mean of precision and recall. The precision, recall, and F-score of shopping-related keywords derived by the proposed methodology were revealed to be higher than those of the entire number of keywords. This study proposes a scheme that is able to obtain shopping-related keywords in a relatively simple manner. We could easily extract shopping-related keywords simply by examining transactions whose next visit is a shopping mall. The resultant shopping-related keyword set is expected to be a useful asset for many shopping malls that participate in keyword marketing. Moreover, the proposed methodology can be easily applied to the construction of special area-related keywords as well as shopping-related ones.

Analysis of Collaborative Research Trends in Library and Information Science in Korea (국내 문헌정보학 분야의 공동연구 동향 분석)

  • Lee, HyeKyung;Yang, Kiduk;Kim, SeonWook
    • Journal of Korean Library and Information Science Society
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    • v.50 no.2
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    • pp.191-214
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    • 2019
  • In order to understand the trends of collaborative research in the field of Library and Information Science (LIS) in Korea, this study analyzed bibliometric data and keywords of 5,383 Journal papers by 195 Korean LIS professors from 2000 to 2017 as well as the author credit allocation formulas of 26 Korean university research evaluation criteria. Examination of university research evaluation criteria revealed co-authors' credit level to be generally much lower than that of single authors, which in turn reduces the relative value of collaborative research. As a result, recent journals publish more co-authored papers than single author papers both domestically and internationally. The study also found collaborative research to be less prevalent in private universities than national universities and least prevalent in associate professors among professors. Furthermore, keyword analysis of study data revealed the emerging topics of both domestic and international collaborative research to be those that reflect social phenomena as well as those that relate to information science employing new technologies.

A Study on Follow-up Survey Methodology to Verify the Effectiveness of (<인생나눔교실> 사업의 효과 검증을 위한 추적 조사 방법론 연구 - 2017~2018년도 영상추적조사를 중심으로 -)

  • Lee, Dong Eun
    • Korean Association of Arts Management
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    • no.53
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    • pp.207-247
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    • 2020
  • is a project for the senior generation with humanistic knowledge to become a mentor and communicate with them to present the wisdom and direction of life to the new generations of mentees based on various life experiences. has been expanding since 2015, starting with the pilot operation in 2014. In general, projects such as these are assessed to establish effectiveness indicators to verify effectiveness and to establish project management and development strategies. However, most of the evaluations have been conducted quantitatively and qualitatively based on the short-term duration of the project. Therefore, in the case of continuous projects such as , especially in the field of culture and arts where long-term effectiveness verification is required, the short-term evaluation is difficult to predict and judge the actual meaningful effects. In this regard, tried to examine the qualitative change of key participants in this project through the 2017 and 2018 image tracking survey. For this purpose, we adopted qualitative research methodology through interview video shooting, field shooting, and value coding as a research method suitable for the research subject. To analyze the results, first, the interview images were transcribed, keywords were extracted, value encoding works were matched with human psychological values, and the theoretical method was used to identify changes and to derive the meaning. In fact, despite the fact that the study conducted in this study was a follow-up survey, it remained a limitation that it analyzed the changed pattern in a rather short time of 2 years. However, this study systemized the specific methodology that researchers should conduct for follow-up and provided the flow of research at the present time when there is hardly a model for follow-up in the field of culture and arts education business in Korea as well as abroad. Significance can be derived from this point. In addition, it can be said that it has great significance in preparing the detailed system and case of comparative analysis methodology through value coding.

Exploring the possibility of using ChatGPT and Stable Diffusion as a tool to recommend picture materials for teaching and learning

  • Soo-Hwan Lee;Ki-Sang Song
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.4
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    • pp.209-216
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    • 2023
  • In this paper, artificial intelligence agents ChatGPT and Stable Diffusion were used to explore the possibility of educational use by implementing a program to recommend picture materials for teaching and learning according to the class topic entered by teachers. The average time spent recommending all picture materials is about 6 minutes. In general, pictures related to keywords were recommended, and the letters in the recommended pictures could only know the intention to represent the letters, and the letters could not be recognized and the meaning could not be known. However, further research seems to be needed on the fact that the type or content of the recommended picture depends entirely on the response of ChatGPT and that it is not possible to accurately recommend the picture for all keywords. In addition, it was concluded that it is true that the recommended picture is related to the keyword, but the evaluation of whether it has educational value is the subject of discussion that should be left to the judgment of human teachers.

Study of Recognition and Spatial Attributes of Gwanghwamun Square - With a Focus on Text Mining and Social Network Analysis - (광화문광장의 인식 분석 연구 - 텍스트마이닝과 소셜네트워크 분석을 중심으로 -)

  • Kyung-Sook Woo;Byoungwook Min;Jin-Pyo Kim
    • Journal of Environmental Impact Assessment
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    • v.32 no.3
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    • pp.187-194
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    • 2023
  • This study identified how users of Gwanghwamun Square perceive the space and derived the spatial attributes of Gwanghwamun Square. There are four spatial attributes of Gwanghwamun Square: preservation of the historical environment, beauty of the surrounding landscape, suitability as a resting place, and activation of recreation. The first attribute, preservation of the historical environment, refers to the spaces that reflect the unique characteristics of Gwanghwamun Square and resonate with culture, including the Blue House, Bukaksan Mountain, Gyeongbok Palace, Yukjo Street, King Sejong, and Yi Sun-sin. The second attribute, beauty of the surrounding landscape, is related to the provision of abundant greenery and natural environment without disturbing the surrounding landscape, and includes landscape, sky, and greenery. The third attribute, suitability as a resting place, refers to various landscape facilities and services to enhance visitor comfort, including tables, chairs, shade, planters, rest areas, and fountains. Finally, recreational activation. This is the provision of various experiences, including exhibitions, performances, experiences, and sightseeing. Utilizing the attributes of Gwanghwamun Plaza derived from this study, it will provide important implications for the reconstruction of Gwanghwamun Plaza if future studies on valuation and estimation of Gwanghwamun Plaza are conducted to verify the differences in preferences by type.

A Study on the Care Needs and Well-being of the Elderly Using Elderly Care Service : Focus on the Social Value Orientation (노인돌봄서비스 이용 노인의 돌봄 욕구와 안녕감에 관한 연구 : 사회적가치지향성의 효과를 중심으로)

  • Kim, Ka-Won;Choi, Sung-hun
    • The Journal of the Korea Contents Association
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    • v.21 no.4
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    • pp.555-564
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    • 2021
  • This study evaluates the social value orientation, well-being of the elderly and care needs of elderly that elderly care services are identified and seeks future service development directions through a desire survey. As of October 2019, 1,501 elderly living alone who used basic care services for the single elderly households for more than 3 months were sampled, and frequency analysis, technical statistical analysis, t-test, and variance analysis were conducted. The survey found that social value orientation averages 90.93, and the sense of well-being of the elderly is 71.29 points. As a result of the analysis of variance and post-hoc analysis, the well-being of the elderly was statistically significant in groups well aware of their social value orientation. In addition, key words such as "loneliness", "lonely Death", and "safety" were derived for concerns that may arise when the service is discontinued. Based on the results of this study, it could be used as basic data to explore the development direction of the new "elderly care services" and to establish a care system for senior citizens in preparation.

Data value extraction through comparison of online big data analysis results and water supply statistics (온라인 빅 데이터 분석 결과와 상수도 통계 비교를 통한 데이터 가치 추출)

  • Hong, Sungjin;Yoo, Do Guen
    • Proceedings of the Korea Water Resources Association Conference
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    • 2021.06a
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    • pp.431-431
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    • 2021
  • 4차 산업혁명의 도래로 사회기반시설물의 계획 및 운영관리에 있어 데이터 분석을 통한 가치추출에 대한 관심은 매우 높은 상황이다. 데이터의 가용성과 접근성, 정부 지원 등을 평가하는 공공데이터 개방지수에서 한국은 1점 만점에 0.93점을 획득하여 경제협력개발기구 회원국 중 1위(2019년 기준)를 할 정도로 매우 높은 수준(평균 0.60점)이다. 그러나 공식적으로 발표 및 배포되는 사회기반시설물 관련 정보와 심도 있는 연구 분석이 필요한 정보는 접근이 여전히 제한적이라 할 수 있다. 특히 대표적인 사회기반시설물인 상수도시스템은 대부분 국가중요시설로 지정되어 있어 다양한 정보를 획득하고 분석하는데 제약이 존재하며, 관련 국가통계인 상수도통계에서는 누수사고 등과 같은 비정상적 상황에 대한 사고지점, 원인 등과 같은 세부정보는 제공하고 있지 않다. 본 연구에서는 웹크롤링 및 빅데이터 분석기술을 활용하여 과거 일정기간 발생한 지자체의 상수도 누수사고 관련 뉴스를 전수조사하고 도출된 사고건수를 국가 공인 정보인 상수도통계자료와 비교·분석하였다. 독립적인 누수사고 기사를 추출하기 위해서 중복기사의 제거, 누수 관련 키워드 정립, 상수도분야 이외의 관련기사 제거 등의 절차가 필요하며, 이와 같은 기법은 R프로그래밍을 통해 구현되었다. 추가적으로 뉴스기사의 자연어 처리기반 정보추출기법을 통해 누수사고 건수 뿐만 아니라 사고발생일, 위치, 원인, 피해정도, 그리고 대상 관로의 크기 등을 획득하여 상수도 통계에서 제시하고 있는 정보보다 많은 가치를 추출하여 연계할 수 있는 방안을 제시하였다. 제시된 방법론을 국내 A광역시에 적용하여 누수사고 건수를 비교한 결과 상수도통계에서 제시하고 있는 누수발생건수와 유사한 규모의 사고건수를 뉴스기사분석을 통해 도출할 수 있었다. 제안된 방법론은 추가적인 정보의 추출이 가능하다는 점에서 향후 활용성이 높을 것으로 기대된다.

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