• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.426-435
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• 2021

This study aims to functionally classify lexical bundles appearing in academic papers on nuclear science and engineering written in English and then analyze the lexical bundles' characteristics compared to those appearing in general academic papers. To this end, the texts of nuclear science and engineering papers were collected and produced as a corpus(c. 1 mil. tokens). Then they were statistically compared through Chi-square tests and standardized residuals with the corpus of general academic papers(c. 750,000 tokens). The results revealed that, compared to general academic papers, the bundles in the stance lexical bundle category were mainly used among the functional lexical bundle in nuclear science and engineering. The use of the lexical bundles lacked much variety. The same type of lexical bundles was 're-used' and 'recycled'. Based on these research results, educational implications for English for Academic Purposes and the further direction of follow-up research were discussed and suggested.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.311-336
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• 2022

This study analyzed the contents of Goodreads review data, which is a social cataloging service with the participation of book users around the world, to identify the preference factors that affect book users' book recommendations in the library information service environment. To understand user preferences from a more detailed point of view, sub-datasets for each rating group, each book, and each user were constructed in the sample selection process. Stratified sampling was also performed based on the result of topic modeling of review text data to include various topics. As a result, a total of 90 preference factors belonging to 7 categories('Content', 'Character', 'Writing', 'Reading', 'Author', 'Story', 'Form') were identified. Also, the general preference factors revealed according to the ratings, as well as the patterns of preference factors revealed in books and users with clear likes and dislikes were identified. The results of this study are expected to contribute to more sophisticated recommendations in future recommendation systems by identifying specific aspects of user preference factors.

• Journal of Creative Information Culture
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• v.5 no.3
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• pp.215-223
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• 2019

The wave of the information age gradually accelerates, and fusion analysis solutions that can utilize these knowledge data according to accumulation of various forms of big data such as large capacity texts, sounds, movies and the like are increasing, Reduction in the cost of storing data accordingly, development of social network service (SNS), etc. resulted in quantitative qualitative expansion of data. Such a situation makes possible utilization of data which was not trying to be existing, and the potential value and influence of the data are increasing. Research is being actively made to present future-oriented education systems by applying these fusion analysis systems to the improvement of the educational system. In this research, we conducted a big data analysis on Twitter, analyzed the natural language of the data and frequency analysis of the word, quantitative measure of how domestic windows education problems and outcomes were done in it as a solution.

• Journal of the Korean Regional Science Association
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• v.39 no.1
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• pp.3-20
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• 2023

This study aims to categorize the 14 major gentrified commercial areas of Seoul and analyze their characteristics based on their sense of place. To achieve this, we conducted hierarchical cluster analysis using text data collected from Naver Blog. We divided the districts into two dimensions: "experience" and "feature" and analyzed their characteristics using LDA (Latent Dirichlet Allocation) of the text data and statistical data collected from Seoul Open Data Square. As a result, we classified the commercial districts of Seoul into 5 categories: 'theater district,' 'traditional cultural district,' 'female-beauty district,' 'exclusive restaurant and medical district,' and 'trend-leading district.' The findings of this study are expected to provide valuable insights for policy-makers to develop more efficient and suitable commercial policies.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.67-80
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• 2022

The purpose of this study is to clarify the meaning and characteristics of re-organized shortform contents, which is centered on media companies to edit and service existing broadcast content. For this, KBS, MBC, SBS, JTBC, and tvN's entire drama videos and representative entertainment programs opened on the Naver TV platform from 2014 to 2021 were selected for analysis and a synchronic and diachronic approach was conducted at the same time. As a result of the analysis, quantitative and qualitative expansion was made, with the number and form of videos provided by both dramas and entertainment programs diversifying from a synchronic approach. In particular, in the case of special videos, the meaning as independent content was also strengthened, such as sequencing centered on characters, themes, and materials. It was confirmed that thumbnails and titles were also formalized as tags as paratexts that act as curation for searches. From a diachronic point of view, it was found that re-organized shortform contents is considered to be character-oriented contents and independent viewing context through comparison with real-time views and original videos. This study is significant as an attempt to capture the meaning and phase change of shortform contents, which was considered incidental.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.391-394
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• 2021

최근 딥러닝(Deep Learning)을 활용하여 텍스트로 표현된 단어나 문장의 의미를 파악하기 위한 다양한 연구가 활발하게 수행되고 있다. 하지만, 딥러닝을 통해 특정 도메인에서 사용되는 언어를 이해하기 위해서는 해당 도메인의 충분한 데이터에 대해 오랜 시간 학습이 수행되어야 한다는 어려움이 있다. 이러한 어려움을 극복하고자, 최근에는 방대한 양의 데이터에 대한 학습 결과인 사전 학습 언어 모델(Pre-trained Language Model)을 다른 도메인의 학습에 적용하는 방법이 딥러닝 연구에서 많이 사용되고 있다. 이들 접근법은 사전 학습을 통해 단어의 일반적인 의미를 학습하고, 이후에 단어가 특정 도메인에서 갖는 의미를 파악하기 위해 추가적인 학습을 진행한다. 추가 학습에는 일반적으로 대표적인 사전 학습 언어 모델인 BERT의 MLM(Masked Language Model)이 다시 사용되며, 마스크(Mask) 되지 않은 단어들의 의미로부터 마스크 된 단어의 의미를 추론하는 형태로 학습이 이루어진다. 따라서 사전 학습을 통해 의미가 파악되어 있는 단어들이 마스크 되지 않고, 신조어와 같이 의미가 알려져 있지 않은 단어들이 마스크 되는 비율이 높을수록 단어 의미의 학습이 정확하게 이루어지게 된다. 하지만 기존의 MLM은 무작위로 마스크 대상 단어를 선정하므로, 사전 학습을 통해 의미가 파악된 단어와 사전 학습에 포함되지 않아 의미 파악이 이루어지지 않은 신조어가 별도의 구분 없이 마스크에 포함된다. 따라서 본 연구에서는 사전 학습에 포함되지 않았던 신조어에 대해서만 집중적으로 마스킹(Masking)을 수행하는 방안을 제시한다. 이를 통해 신조어의 의미 학습이 더욱 정확하게 이루어질 수 있고, 궁극적으로 이러한 학습 결과를 활용한 후속 분석의 품질도 향상시킬 수 있을 것으로 기대한다. 영화 정보 제공 사이트인 N사로부터 영화 댓글 12만 건을 수집하여 실험을 수행한 결과, 제안하는 신조어 표적 마스킹(NTM: Newly Coined Words Target Masking)이 기존의 무작위 마스킹에 비해 감성 분석의 정확도 측면에서 우수한 성능을 보임을 확인하였다.

• Design Convergence Study
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• v.15 no.1
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• pp.233-246
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• 2016

Mobile health industry has been combined with IT technology and is attracting attention. The health application has been developed to provide users a healthy life style. First of all, 5 mobile health applications were selected and reviewed in terms of their service trend. It turned out that none of those applications had any emotional data but physical one. Secondly, to extract users' emotion, technological researches were sorted into different categories. And the result implied that text-based emotion recognition technology is the most suitable for the mobile health service. To implement the service, the application was designed and developed the process of emotion recognition system based on the contents of the research. One-dimension emotion model, which is the standard of classifying emotional data and social network service, was set up as a source. In last, to suggest the usage of health application has been combined with persuasive technology. As a result, this paper prospered a overall service process, concrete service scheme and a guidelines containing 15 services in accordance with the five emotions and time. It is expected to become a direction for indicators considering a psychological individual context.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.210-211
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• 2020

COVID-19으로 인해 국민들에게 전달되는 재난정보의 양상이 서서히 변화하고 있다. 이는 정보통신의 발전 양상과도 매우 깊은 관계를 가지고 있다고 볼 수 있다. 이전까지의 정부 및 지자체에서 제공되는 재난정보에 대한 형태는 문자와 음성으로만 제공하므로써 고령자와 외국인과 같은 재난 약자에게 명확한 상황인지를 하기에 어려움이 있었다. 이를 해결하기 위한 전방위적인 노력을 하고 있으며, 보다 정확하고 보다 다양한 정보를 제공하고자 관련 연구를 수행하고 있다. 이는 급속도로 발전하는 정보통신 매체(UHD 및 5G, 오픈스크린 등)를 기반으로 국민들로 하여금 신속.정확한 재난상황인지를 가능케 할 수 있다. 이로 인한 재난경보 관련 최근 이슈는 '내 위치 맞춤형 정보'와 '다매체 정보'가 아닐까 싶다. 정보통신 매체가 발달함에 따라 제공되는 재난경보의 범위가 내 위치를 기준으로 좁아지며, 시각적으로 직관적인 콘텐츠를 제공할 수 있다. 이는 각 매체의 고유 정보를 통해 위치가 확인 가능하면서 해당 지역에 맞는 정보만 선택적으로 취함으로써 불필요한 정보를 제공하지 않게 된다. 본 연구를 통해 이러한 부분을 해결하기 위해 TTA에서 표준으로 제정된 CAP (Common Alerting Protocol)을 활용하였으며, 'Area' 항목에 지역코드(전국~읍면동)를 함께 포함함으로써 가능해졌다. 또한 CAP을 활용함에 따라 텍스트부터 음성, 이미지, 웹 콘텐츠까지 최신의 영상 매체에 적용 가능한 재난정보 콘텐츠를 제공 가능해졌으며, 특히 UHD 및 5G, 오픈스크린과 같은 통신 네트워크 기반 영상 매체에 적합한 멀티미디어 재난정보 콘텐츠를 제공할 수 있다. 제공된 콘텐츠에는 각종 관련 정보를 확인 가능하도록 링크를 제공하여 필요에 따라 보다 자세한 재난정보를 확인할 수 있다. 이를 기반으로 재난경보에 대한 다변화를 통해 나에게 꼭 필요한 정보가 제공될 수 있도록 발령 체계 개편이 필요하다.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.1-11
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• 2023

The purpose of this study is to develop a discussion-centered teaching and learning model for nurturing creative and convergence talents. Regarding the research method, a draft model on discussion-centered teaching and learning was devised, and the model was completed through expert validation. The final draft was revised and supplemented by verifying how valid the model was when applied in class by using the derived final draft. Compared with the draft on discussion-centered teaching and learning model, the final model focused on text-reading emphasis, methods of questioning, and question generation strategies, excluding jigsaw discussions. The discussion-centered teaching and learning model developed in this study is expected to help instructors foster creative and convergence talents. Three suggestions have been provided to effectively apply this model to the field. First, an attitude of listening and respect is required during a discussion. Second, a plan should be considered on how to induce active participation of learners participating in the discussion. Third, the importance of managing discussion time was emphasized.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.187-195
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• 2023

This study propose to develop artificial intelligence liberal arts courses for college students in the humanities and social sciences majors using the entry artificial intelligence model. A group of experts in computer, artificial intelligence, and pedagogy was formed, and the final artificial intelligence liberal arts course was developed using previous research analysis and Delphi techniques. As a result of the study, the educational topics were largely composed of four categories: image classification, image recognition, text classification, and sound classification. The training consisted of 1) Understanding the principles of artificial intelligence, 2) Practice using the entry artificial intelligence model, 3) Identifying the Ethical Impact, and 4) Based on learned, team idea meeting to solve real-life problems. Through this course, understanding the principles of the core technology of artificial intelligence can be directly implemented through the entry artificial intelligence model, and furthermore, based on the experience of solving various real-life problems with artificial intelligence, and it can be expected to contribute positively to understanding technology, exploring the ethics needed in the artificial intelligence era.