• Title/Summary/Keyword: 텍스트 연구

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A Study on the user attributes for acquisition of information by analyzing the durability of real-time issues (실시간 이슈의 지속성 분석을 통한 사용자 정보 습득에 대한 특성과 패턴에 대한 연구)

  • Oh, Junyep;Lee, Seungkyu;Lee, Jooyoup
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.7 no.4
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    • pp.299-314
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    • 2017
  • Technological advances in media have expanded users' consciousness. At the same time, users have changed from passive into active voice by interacting media. The emergence of mobile made different structures and contents compared to the past. Especially, Korean culture of mobile converted original media channels to contents in a category. Plus, the usage structure of internet of this time converges in massive portal sites. It is because that the structure has aspect of emitting through remediation in the sites. Also, Korean massive portal sites have provided specific service named 'real-time issues'. This is not only the unique way of offering information that exists in Korea but also high usability of getting issues. We therefore considered the meaning of durability of real-time issues in the view of journalism, compared original media channels. Then, this paper identified the user attributes for acquisition of information following ways using informal and formal data from Korean massive portal sites named 'Daum' and 'Naver'.

An Integral Approach in Liberal Arts Curriculum of Higher Education - A Case Study on Physical Education Based on the Somatics (대학교양 교육과정 개발의 융합적 접근 - 소매틱스(Somatics)에 기반한 체육교양강좌 사례연구)

  • Lim, Sujin;Kim, Sooyeon
    • 한국체육학회지인문사회과학편
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    • v.57 no.3
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    • pp.117-133
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    • 2018
  • The purpose of this study was to explore integrated approaches to physical education in general education by examining methodology of physical education aiming for convergence education. This case study was conducted, using a qualitative approach during March, 2017 to November, 2017. Data were collected through non-participant observation, in-depth interviews, field-notes, students' journal, syllabus and lecture materials. The key findings are as follows: First, "Emotion Coaching through Movement" is a course of 'understanding of body' approaching integrated humanities science and natural science. Second, it is a convergence education, conducting 'text to daily practice' by approaching positive psychology and neurophysiology. Third, it is a physical education with 'integrated theory and practice' in higher education. These results indicate that students can understand their own body, observe their daily and fixed movement or reaction pattern, and enhance the ability of understanding others through a physical education in general education.

Liaohe National Park based on big data visualization Visitor Perception Study

  • Qi-Wei Jing;Zi-Yang Liu;Cheng-Kang Zheng
    • Journal of the Korea Society of Computer and Information
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    • v.28 no.4
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    • pp.133-142
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    • 2023
  • National parks are one of the important types of protected area management systems established by IUCN and a management model for implementing effective conservation and sustainable use of natural and cultural heritage in countries around the world, and they assume important roles in conservation, scientific research, education, recreation and driving community development. In the context of big data, this study takes China's Liaohe National Park, a typical representative of global coastal wetlands, as a case study, and using Python technology to collect tourists' travelogues and reviews from major OTA websites in China as a source. The text spans from 2015 to 2022 and contains 2998 reviews with 166,588 words in total. The results show that wildlife resources, natural landscape, wetland ecology and the fishing and hunting culture of northern China are fully reflected in the perceptions of visitors to Liaohe National Park; visitors have strong positive feelings toward Liaohe National Park, but there is still much room for improvement in supporting services and facilities, public education and visitor experience and participation.

Depaysement and Its Dreams for a Hallucinative Allegory in Luis Bunuel's Films : "The Discreet Charm of the Bourgeoisie" and "The Phantom of Liberty" (루이스 부뉴엘의 영화에서 나타난 데페이즈망과 몽상의 알레고리 - <부르주와의 은밀한 매력>과 <자유의 환상>을 중심으로 -)

  • Hong, Myung-Hee
    • Journal of Korea Entertainment Industry Association
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    • v.13 no.6
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    • pp.135-142
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    • 2019
  • This study explores the ways in which depaysement and its dreams function as a hallucinative allegory on the basis of the spiritual freedom of surrealism in Luis Bunuel's films: "The Discreet Charm of the Bourgeoisie" and "The Phantom of Liberty". In order to grasp the appearances of the sign in the scene of these films, it examines how he uses surrealism's dépaysement techniques such as the disposition of floating object, bipolarity, and physical contradictions of images. These emerging aesthetic views are as follows: the antipathy to reason, the critique of law and order, the aversion to ideology, and state apparatus. These finally aim at criticizing fundamental irrationality, thus paving a path for opening the possibility of liberation. He laid the foundation for a surrealist film by appropriatizing surrealist techniques to spread his claims. Therefore, this study argues that filmic scenes of dreams and hallucinations for a hallucinative allegory are closely related with the technique of depaysement network which summons the significance of surrealistic freedom in these films.

Maritime Safety Tribunal Ruling Analysis using SentenceBERT (SentenceBERT 모델을 활용한 해양안전심판 재결서 분석 방법에 대한 연구)

  • Bori Yoon;SeKil Park;Hyerim Bae;Sunghyun Sim
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.7
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    • pp.843-856
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    • 2023
  • The global surge in maritime traffic has resulted in an increased number of ship collisions, leading to significant economic, environmental, physical, and human damage. The causes of these maritime accidents are multifaceted, often arising from a combination of crew judgment errors, negligence, complexity of navigation routes, weather conditions, and technical deficiencies in the vessels. Given the intricate nuances and contextual information inherent in each incident, a methodology capable of deeply understanding the semantics and context of sentences is imperative. Accordingly, this study utilized the SentenceBERT model to analyze maritime safety tribunal decisions over the last 20 years in the Busan Sea area, which encapsulated data on ship collision incidents. The analysis revealed important keywords potentially responsible for these incidents. Cluster analysis based on the frequency of specific keyword appearances was conducted and visualized. This information can serve as foundational data for the preemptive identification of accident causes and the development of strategies for collision prevention and response.

Characteristics and Changes of Policy Responses to Local Extinction: A Case of Comprehensive Strategy and Basic Policy on Community-Population-Job Creation in Japan (지방소멸 대응 정책의 특징 및 변화 분석: 일본의 마을·사람·일자리 창생 종합전략 및 기본방침을 사례로)

  • Jang, Seok-Gil Denver;Yang, Ji-Hye;Gim, Tae-Hyoung Tommy
    • Journal of the Korean Regional Science Association
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    • v.40 no.1
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    • pp.37-51
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    • 2024
  • To respond to local extinction, South Korea, under the leadership of the Ministry of the Interior and Safety, identified depopulated areas in 2021 and launched the Local Extinction Response Fund in 2022. However, due to its early stage of implementation, analyzing the characteristics and changes of policy response to local extinction at the central government level remains a challenge. In contrast, Japan, facing similar issues of local extinction as South Korea, has established a robust central government-led response system based on the Regional Revitalization Act and the Comprehensive Strategy and Basic Policy on Community-Population-Job Creation. Hence, this study examines Japan's policy responses to local extinction by analyzing the first and second periods of the Comprehensive Strategy and Basic Policy on Community-Population-Job Creation. For the analysis, topic modeling was employed to enhance text analysis efficiency and accuracy, complemented by expert interviews for validation. The results revealed that the first-period strategy's topics encompassed economy and society, start-up, local government, living condition, service, and industry. Meanwhile, the second-period strategy's topics included resource, the New Normal, woman, digital transformation, industry, region, public-private partnership, and population. The analysis highlights that the policy target, policy direction, and environmental change significantly influenced these policy shifts.

An Investigation Into the Effects of AI-Based Chemistry I Class Using Classification Models (분류 모델을 활용한 AI 기반 화학 I 수업의 효과에 대한 연구)

  • Heesun Yang;Seonghyeok Ahn;Seung-Hyun Kim;Seong-Joo Kang
    • Journal of the Korean Chemical Society
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    • v.68 no.3
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    • pp.160-175
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    • 2024
  • The purpose of this study is to examine the effects of a Chemistry I class based on an artificial intelligence (AI) classification model. To achieve this, the research investigated the development and application of a class utilizing an AI classification model in Chemistry I classes conducted at D High School in Gyeongbuk during the first semester of 2023. After selecting the curriculum content and AI tools, and determining the curriculum-AI integration education model as well as AI hardware and software, we developed detailed activities for the program and applied them in actual classes. Following the implementation of the classes, it was confirmed that students' self-efficacy improved in three aspects: chemistry concept formation, AI value perception, and AI-based maker competency. Specifically, the chemistry classes based on text and image classification models had a positive impact on students' self-efficacy for chemistry concept formation, enhanced students' perception of AI value and interest, and contributed to improving students' AI and physical computing abilities. These results demonstrate the positive impact of the Chemistry I class based on an AI classification model on students, providing evidence of its utility in educational settings.

A School-tailored High School Integrated Science Q&A Chatbot with Sentence-BERT: Development and One-Year Usage Analysis (인공지능 문장 분류 모델 Sentence-BERT 기반 학교 맞춤형 고등학교 통합과학 질문-답변 챗봇 -개발 및 1년간 사용 분석-)

  • Gyeongmo Min;Junehee Yoo
    • Journal of The Korean Association For Science Education
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    • v.44 no.3
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    • pp.231-248
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    • 2024
  • This study developed a chatbot for first-year high school students, employing open-source software and the Korean Sentence-BERT model for AI-powered document classification. The chatbot utilizes the Sentence-BERT model to find the six most similar Q&A pairs to a student's query and presents them in a carousel format. The initial dataset, built from online resources, was refined and expanded based on student feedback and usability throughout over the operational period. By the end of the 2023 academic year, the chatbot integrated a total of 30,819 datasets and recorded 3,457 student interactions. Analysis revealed students' inclination to use the chatbot when prompted by teachers during classes and primarily during self-study sessions after school, with an average of 2.1 to 2.2 inquiries per session, mostly via mobile phones. Text mining identified student input terms encompassing not only science-related queries but also aspects of school life such as assessment scope. Topic modeling using BERTopic, based on Sentence-BERT, categorized 88% of student questions into 35 topics, shedding light on common student interests. A year-end survey confirmed the efficacy of the carousel format and the chatbot's role in addressing curiosities beyond integrated science learning objectives. This study underscores the importance of developing chatbots tailored for student use in public education and highlights their educational potential through long-term usage analysis.

Evaluation of the readability of self-reported voice disorder questionnaires (자기보고식 음성장애 설문지 문항의 가독성 평가)

  • HyeRim Kwak;Seok-Chae Rhee;Seung Jin Lee;HyangHee Kim
    • Phonetics and Speech Sciences
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    • v.16 no.1
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    • pp.41-48
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    • 2024
  • The significance of self-reported voice assessments concerning patients' chief complaints and quality of life has increased. Therefore, readability assessments of questionnaire items are essential. In this study, readability analyses were performed based on text grade and complexity, vocabulary frequency and grade, and lexical diversity of the 11 Korean versions of self-reported voice disorder questionnaires (KVHI, KAVI, KVQOL, K-SVHI, K-VAPP, K-VPPC, TVSQ, K-VDCQ, K-VFI, K-VTDS, and K-VoiSS). Additionally, a comparative readability assessment was conducted on the original versions of these questionnaires to discern the differences between their Korean counterparts and the questionnaires for children. Consequently, it was determined that voice disorder questionnaires could be used without difficulty for populations with lower literacy levels. Evaluators should consider subjects' reading levels when conducting assessments, and future developments and revisions should consider their reading difficulties.

Enhancing Empathic Reasoning of Large Language Models Based on Psychotherapy Models for AI-assisted Social Support (인공지능 기반 사회적 지지를 위한 대형언어모형의 공감적 추론 향상: 심리치료 모형을 중심으로)

  • Yoon Kyung Lee;Inju Lee;Minjung Shin;Seoyeon Bae;Sowon Hahn
    • Korean Journal of Cognitive Science
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    • v.35 no.1
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    • pp.23-48
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    • 2024
  • Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.