• Title/Summary/Keyword: 관심어

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The Trend and Tasks of Meister High School Research: Network Text Analysis and Content Analysis (마이스터고 연구의 동향과 과제: 네트워크 텍스트 분석 및 내용분석)

  • Bae, Sang Hoon;Jang, Chang Seong;Lee, Tae Hee;Cho, Sung Bum
    • Journal of vocational education research
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    • v.33 no.3
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    • pp.83-104
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    • 2014
  • The study examined the trends of research on Meister high schools in Korea. The study also investigated differences of research interests between the university faculty and graduate students who are the future researchers in this field. A total of 56 research articles were analyzed using the network text analysis method and the content analysis. The results showed that 56% of all studies was done to reveal the distinguishable characteristics of Meister students and teachers compared to their counterpart in vocational schools. 17.6% of studies were about school curriculum, while 14.0% of studies were on school organization and operation. Only 12.3% of studies were conducted to evaluate school performance. Quantitative studies outnumbered qualitative ones. Based on the results, this study suggested implications for policies and future research on meister high school.

A Big-Data Analysis on Older Adult's Health and Safety Issues (노인의 건강 및 안전문제에 대한 빅데이터 분석)

  • Wang, Lin;Lee, Ju-Gyung;Hwang, Ji-Hyeon
    • The Journal of the Korea Contents Association
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    • v.19 no.4
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    • pp.336-344
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    • 2019
  • Currently, Korea is entering an aging society, causing the issues of older adults in a wide range of fields. This study focuses on the health and safety issues of the older adults. As a theoretical background, Maslow's hierarchy of needs theory was applied, and a new theory was established in connection with the physiological needs and safety needs of the 5 stages of desire in relation to the health and safety issues of the older adults. Health issues applying to physiological needs for the older adults are examined in detail in the body, perception and psychology areas, and safety accidents occurring indoors and outdoors are examined in relation to safety needs. Naver DataLab, a big data portal, shows that the number of bugs regarding health and safety of the older adults is steadily increasing. And through Google Trends, we can understand the interest setting up related search keyword about the older adults. According to the related search keywords, social part related to health in health issues is ranked high and kewords related to accident type in safety issues is ranked high. These findings will be an important basis data for research and solution to the issues of older adults.

A Study on Changes in Media Report of Police Assigned for Special Guard Using Big Kinds

  • Park, Su-Hyeon;Cho, Cheol-Kyu
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.6
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    • pp.167-172
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    • 2021
  • The objective of this study is to present the academic implications and developmental direction of the police assigned for special guard system through big data analysis on the objective and macroscopic viewpoint of the media. As research method, this study conducted the analysis on 'police assigned for special guard' and the analysis of related words that would visualize the keywords highly related to keyword trend and news. Also, after dividing the period into the 1990s, 2000s, and 2010s, the number of relevant articles in each period was drawn for understanding the flow. In the results of this study, the perception of media report of police assigned for special guard was about the recruitment of police assigned for special guard, and relevant events/accidents, which showed the coexistence of positive interest in the recruitment of police assigned for special guard and negative image of events/accidents related to police assigned for special guard. As a result, however, the necessity and demand for police assigned for special guard are increasing. Thus, the police assigned for special guard should be engaged in work after carefully thinking of its role in charge of ethical responsibility and safety as an axis for maintaining the national safety and social order.

Problems with the use of a Neologism in media and ways to improve them (언론미디어의 신어(新語) 사용 문제와 개선 방안)

  • Bang, MeeYoung;Lee, GunWoong
    • The Journal of the Convergence on Culture Technology
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    • v.8 no.1
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    • pp.191-200
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    • 2022
  • This study analyzes the perception survey of the general public on the problems of a neologism(new words), which are frequently used in media media, and derives improvement measures and implications based on the data. In general, it can be seen that the creed is exposed and used indiscriminately through media, and those in their 20s and 30s are positive for the use of new words and those in their 50s and 60s are relatively negative. The biggest problem is that excessive use of creed can cause conflict and alienation between generations, and the need for correct Korean use is recognized overall as it can enhance Hangeul destruction and inappropriate social awareness. However, media outlets often use new words in a positive way to induce interest and enrich content by using them in the right place for the latest trends, such as small but certain happiness. As an alternative to this problem, self-purification of media workers is the most important, and it is recommended to encourage proper use of Korean through media literacy education and campaigns.

Improving Twitter Search Function Using Twitter API (트위터 API를 활용한 트위터 검색 기능 개선)

  • Nam, Yong-Wook;Kim, Yong-Hyuk
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.3
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    • pp.879-886
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    • 2018
  • The basic search engine on Twitter shows not only tweets that contain search keywords, but also all articles written by users with nicknames containing search keywords. Since the tweets unrelated to the search keyword are exposed as search results, it is inconvenient to many users who want to search only tweets that include the keyword. To solve this inconvenience, this study improved the search function of Twitter by developing an algorithm that searches only tweets that contain search keywords. The improved functionality is implemented as a Web service using ASP.NET MVC5 and is available to many users. We used a powerful collection method in C# to retrieve the results of an object, and it was also possible to output them according to the number of 'retweets' or 'favorites'. If the number of retrieved numbers is less than a given number, we also added an exclusion filter function. Thus, sorting search results by the number of retweets or favorites, user can quickly search for opinions that are of interest to many users. It is expected that many users and data analysts will find the developed function convenient to search on Twitter.

Research Trend Analysis of Publications in the Journal of Home Economics Education Association Using Network Text Analysis (네트워크 텍스트 분석을 이용한 한국가정과교육학회지 논문의 연구 동향 분석)

  • Lee, Yoon-Jung;Kim, Eun Jeung;Kim, Ji sun
    • Journal of Korean Home Economics Education Association
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    • v.31 no.4
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    • pp.1-18
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    • 2019
  • The purpose of this study was to analyze the research trend in home economics education using network text analysis method. The 586 research articles published in the Journal of Home Economics Education Association between July, 2003 and December 2018 were examined using Neckinger 4, a social network analysis software. The frequency and centrality measures(degree centrality, closeness centrality, and betweenness centrality) were calculated for the words appeared throughout the whole period, and the centrality analysis and LAD(Latent Dirichlet Allocation) were conducted for the four sub-periods. The results are as follows: first, the most frequently appeared words are parents, culture, unit, health, career, consumption, practicality, etc. The words such as parents and management scored high in degree centrality; parents and male students in closeness centrality; and male students and units in betweenness centrality. Second, when divided into four periods, the words such as education, family, purpose, class, middle school, and school appeared most frequently across the periods; but some words such as 'purpose' (in period 3 and 4), or 'process' (in period 4) were salient only in certain periods. Third, the words with high centrality were consistent regardless of the types of centrality within each period. Fourth, the topic analysis using LAD showed that curriculum, textbook, family healthiness, teaching-learning, evaluation, dietary life, appearance management, and consumption were the topics consistently appeared across all periods. The topics have become diversified and deepened. New topics such as teacher training and safety appeared in later periods, possibly due to the curriculum and national policy changes, and housing as a less represented topic is suggested as an area that needs further research attention. This study has implication in that it allows researchers to identify the major research interests and the trends in research by researchers in home economic education.

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.

Analyzing Global Startup Trends Using Google Trends Keyword Big Data Analysis: 2017~2022 (Google Trends 의 키워드 빅데이터 분석을 활용한 글로벌 스타트업 트렌드 분석: 2017~2022 )

  • Jaeeog Kim;Byunghoon Jeon
    • Journal of Platform Technology
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    • v.11 no.4
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    • pp.19-34
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    • 2023
  • In order to identify the trends and insights of 'startups' in the global era, we conducted an in-depth trend analysis of the global startup ecosystem using Google Trends, a big data analysis platform. For the validity of the analysis, we verified the correlation between the keywords 'startup' and 'global' through BIGKinds. We also conducted a network analysis based on the data extracted using Google Trends to determine the frequency of searches for the keyword or term 'startup'. The results showed a strong positive linear relationship between the keywords, indicating a statistically significant correlation (correlation coefficient: +0.8906). When exploring global startup trends using Google Trends, we found a terribly similar linear pattern of increasing and decreasing interest in each country over time, as shown in Figure 4. In particular, startup interest was low in the range of 35 to 76 from mid-2020 due to the COVID-19 pandemic, but there was a noticeable upward trend in startup interest after March 2022. In addition, we found that the interest in startups in each country except South Korea is very similar, and the related topics are startup company, technology, investment, funding, and keyword search terms such as best startup, tech, business, invest, health, and fintech are highly correlated.

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The Topic-Rank Technique for Enhancing the Performance of Blog Retrieval (블로그 검색 성능 향상을 위한 주제-랭크 기법)

  • Shin, Hyeon-Il;Yun, Un-Il;Ryu, Keun-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.1
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    • pp.19-29
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    • 2011
  • As people have heightened attention to blogs that are individual media, a variety rank algorithms was proposed for the blog search. These algorithms was modified for structural features of blogs that differ from typical web sites, and measured blogs' reputations or popularities based on the interaction results like links, comments or trackbacks and reflected in the search system. But actual blog search systems use not only blog-ranks but also search words, a time factor and so on. Nevertheless, those might not produce desirable results. In this paper, we suggest a topic-rank technique, which can find blogs that have significant degrees of association with topics. This technique is a method which ranks the relations between blogs and indexed words of blog posts as well as the topics representing blog posts. The blog rankings of correlations with search words are can be effectively computed in the blog retrieval by the proposed technique. After comparing precisions and coverage ratios of our blog retrieval system which applis our proposed topic-rank technique, we know that the performance of the blog retrieval system using topic-rank technique is more effective than others.

Study on Zero-shot based Quality Estimation (Zero-Shot 기반 기계번역 품질 예측 연구)

  • Eo, Sugyeong;Park, Chanjun;Seo, Jaehyung;Moon, Hyeonseok;Lim, Heuiseok
    • Journal of the Korea Convergence Society
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    • v.12 no.11
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    • pp.35-43
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    • 2021
  • Recently, there has been a growing interest in zero-shot cross-lingual transfer, which leverages cross-lingual language models (CLLMs) to perform downstream tasks that are not trained in a specific language. In this paper, we point out the limitations of the data-centric aspect of quality estimation (QE), and perform zero-shot cross-lingual transfer even in environments where it is difficult to construct QE data. Few studies have dealt with zero-shots in QE, and after fine-tuning the English-German QE dataset, we perform zero-shot transfer leveraging CLLMs. We conduct comparative analysis between various CLLMs. We also perform zero-shot transfer on language pairs with different sized resources and analyze results based on the linguistic characteristics of each language. Experimental results showed the highest performance in multilingual BART and multillingual BERT, and we induced QE to be performed even when QE learning for a specific language pair was not performed at all.