• 제목/요약/키워드: Keyword Evaluation

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Predicting Movie Revenue by Online Review Mining: Using the Opening Week Online Review (영화 흥행성과 예측을 위한 온라인 리뷰 마이닝 연구: 개봉 첫 주 온라인 리뷰를 활용하여)

  • Cho, Seung Yeon;Kim, Hyun-Koo;Kim, Beomsoo;Kim, Hee-Woong
    • Information Systems Review
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    • v.16 no.3
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    • pp.113-134
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    • 2014
  • Since a movie is an experience goods, purchase can be decided upon preliminary information and evaluation. There are ongoing researches on what impact online reviews might have on movie revenues. Whereas research in the past was focused on the effect of online reviews. The influence of online reviews appears to be significant in products like a movie because it is difficult to evaluate the feature prior to "consuming" the product. Since an online review is regarded to be objective, consumers find it more trustworthy. Contrary to prior research focused on movie review ratings and volume, we focus moves on movie features related specific reviews. This research proposes a predictive model for movie revenue generation. We decided 15 criteria to classify movie features collected from online reviews through the online review mining and made up feature keyword list each criterion. In addition, we performed data preprocessing and dimensional reduction for data mining through factor analysis. We suggest the movie revenue predictive model is tested using discriminant analysis. Following the discriminant analysis, we found that online review factors can be used to predict movie popularity and revenue stream. We also expect using this predictive model, marketers and strategic decision makers can allocate their resources in more parsimonious fashion.

Investigation on the reality of school mathematics based on the learner's competencies (학습자의 핵심역량에 기초한 수학교육 실태 탐색 - 뉴질랜드와 프랑스를 중심으로 -)

  • Choe, Seung-Hyun;Hwang, Hye-Jeang;Nam, Geum-Cheon
    • Journal of the Korean School Mathematics Society
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    • v.15 no.2
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    • pp.215-238
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    • 2012
  • One of the keyword in every nation's recent educational policy is key competencies. Considering national competitiveness originating from educational competitiveness, educational policy has been driven to identify key competencies and realize them through school education. Within this context some leading countries have developed competencies-based curriculum and discussed ways to relate key competencies and subject matter areas. However, there have been few researches on how to reflect or integrate key competencies into subject matter areas. Because of this reason, the ways to incorporate and integrate key competencies into three subject areas including mathematics were investigated. The recent trends of curriculum, teaching and learning, and assessment of domestic and foreign cases were explored by the subject of one Korean international middle school, one British foreign school in Seoul, one French foreign school in Seoul, and four middle schools in New Zealand. To establish competencies-based school education, there should be intimate connection system among curriculum, teaching and learning, assessment, and teacher education. Through analysis of domestic and foreign cases, some conclusions regarding how these aspects have changed with the emphasis of key competencies were drawn. In this paper, through classroom observations and teacher interviews, the reality of competencies-based mathematics teaching of New Zealand and France was investigated. As a result, summaries and recommendations related to ways to improve subject teaching and teacher education in light of key competencies were presented. In these recommendations, the ways to reconstruct subject-based curriculum, the content-specific teaching and learning, and educational assessment were included.

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Design and Implementation of a Question Management System based on a Concept Lattice (개념 망 구조를 기반으로 한 문항 관리 시스템의 설계 및 구현)

  • Kim, Mi-Hye
    • The Journal of the Korea Contents Association
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    • v.8 no.11
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    • pp.412-425
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    • 2008
  • One of the important elements for improving academic achievement of learners in education through e-learning is to support learners to study by finding questions they want with providing various evaluation questions. However, most of question retrieval systems usually depend on keyword search based on only a syntactical analysis and/or a hierarchical browsing system classified by the topics of subjects. In such a system it is not easy to find integrative questions associated with each other. In order to improve this problem, in this paper we proposed a question management and retrieval system which allows users to easily manage questions and also to effectively find questions for study on the Web. Then, we implemented a system that gives to access questions for the domain of C language programming. The system makes it possible to easily search questions related to not only a single theme but also questions integrated by interrelationship between topics and questions. This is done by supporting to be able to retrieve questions according to conceptual interrelationships between questions from user query. Consequently, it is expected that the proposed system will provide learners to understand the basic theories and the concepts of the subjects as well as to improve the ability of comprehensive knowledge utilization and problem-solving.

The Study on the Paradigm Change of Policy Making in the field of Korean Content Industry (문화콘텐츠 정책평가와 개선방안에 관한 연구)

  • Shim, Sang-Min
    • Review of Culture and Economy
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    • v.17 no.2
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    • pp.103-135
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    • 2014
  • This research dwells on the new paradigm of policy making of some innovative nations in Korean content industry. Especially this paper did evaluation of governmental policy in recent 5 years (2008~2012) in the field of Korean content industry. According to this research, the program of policy in Korean content industry had been obsessed to passive enrichment focusing on some part of content industry. The whole process of policy, scheme of policy and working flow of policy were very constrained in order to encourage more measurable area like CT(culture technology). Thus, we need new strong policy in this new government launched in 2013. The apparent keyword should be 'management'. New activity of policy need to focus on encourage Korean content industry in the real site of field, not in bureaucratic office in remote site. This change reflecting real filed management system would be productive innovation for policy making and activity in Korea.

Video-to-Video Generated by Collage Technique (콜라주 기법으로 해석한 비디오 생성)

  • Cho, Hyeongrae;Park, Gooman
    • Journal of Broadcast Engineering
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    • v.26 no.1
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    • pp.39-60
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    • 2021
  • In the field of deep learning, there are many algorithms mainly after GAN in research related to generation, but in terms of generation, there are similarities and differences with art. If the generation in the engineering aspect is mainly to judge the presence or absence of a quantitative indicator or the correct answer and the incorrect answer, the creation in the artistic aspect creates a creation that interprets the world and human life by cross-validating and doubting the correct answer and incorrect answer from various perspectives. In this paper, the video generation ability of deep learning was interpreted from the perspective of collage and compared with the results made by the artist. The characteristic of the experiment is to compare and analyze how much GAN reproduces the result of the creator made with the collage technique and the difference between the creative part, and investigate the satisfaction level by making performance evaluation items for the reproducibility of GAN. In order to experiment on how much the creator's statement and purpose of expression were reproduced, a deep learning algorithm corresponding to the statement keyword was found and its similarity was compared. As a result of the experiment, GAN did not meet much expectations to express the collage technique. Nevertheless, the image association showed higher satisfaction than human ability, which is a positive discovery that GAN can show comparable ability to humans in terms of abstract creation.

Counseling Outcomes Research Trend Analysis Using Topic Modeling - Focus on 「Korean Journal of Counseling」 (토픽 모델링을 활용한 상담 성과 연구동향 분석 - 「상담학연구」 학술지를 중심으로)

  • Park, Kwi Hwa;Lee, Eun Young;Yune, So Jung
    • Journal of Digital Convergence
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    • v.19 no.11
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    • pp.517-523
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    • 2021
  • The outcome of the consultation is important to both the counselor and the researcher. Analyzing the trends of research on the results of counseling that have been carried out so far will help to comprehensively structure the results of consultations. The purpose of this research is to analyze research trends in Korea, focusing on research related to the outcomes of counseling published in 「Korean Journal of Counseling」 from 2011 to 2021, which is one of the well-known academic journals in the field of counseling in Korea. This is to explore the direction of future research by navigating the knowledge structure of research. There were 197 studies used for analysis, and the final 339 keyword were extracted during the node extraction process and used for analysis. As a result of extracting potential topics using the LDA algorithm, "Measurement and evaluation of counseling outcomes", "emotions and mediate factors affecting interpersonal relationships", and "career stress and coping strategies" are the main topics. Identifying major topics through trend analysis of counseling performance research contributed to structuring counseling performance. In-depth research on these topics needs to continue thereafter.

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.

Understanding of Generative Artificial Intelligence Based on Textual Data and Discussion for Its Application in Science Education (텍스트 기반 생성형 인공지능의 이해와 과학교육에서의 활용에 대한 논의)

  • Hunkoog Jho
    • Journal of The Korean Association For Science Education
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    • v.43 no.3
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    • pp.307-319
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    • 2023
  • This study aims to explain the key concepts and principles of text-based generative artificial intelligence (AI) that has been receiving increasing interest and utilization, focusing on its application in science education. It also highlights the potential and limitations of utilizing generative AI in science education, providing insights for its implementation and research aspects. Recent advancements in generative AI, predominantly based on transformer models consisting of encoders and decoders, have shown remarkable progress through optimization of reinforcement learning and reward models using human feedback, as well as understanding context. Particularly, it can perform various functions such as writing, summarizing, keyword extraction, evaluation, and feedback based on the ability to understand various user questions and intents. It also offers practical utility in diagnosing learners and structuring educational content based on provided examples by educators. However, it is necessary to examine the concerns regarding the limitations of generative AI, including the potential for conveying inaccurate facts or knowledge, bias resulting from overconfidence, and uncertainties regarding its impact on user attitudes or emotions. Moreover, the responses provided by generative AI are probabilistic based on response data from many individuals, which raises concerns about limiting insightful and innovative thinking that may offer different perspectives or ideas. In light of these considerations, this study provides practical suggestions for the positive utilization of AI in science education.

Effects of Franchise Restaurant Selection Attributes on Perceived Value, Customer Satisfaction and Loyalty (프랜차이즈 레스토랑의 선택속성이 지각된 가치와 고객만족 및 고객충성도에 미치는 영향)

  • Wang, Shuo;Lee, Yong-Ki;Kim, Sung-Hwan
    • The Korean Journal of Franchise Management
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    • v.9 no.4
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    • pp.7-19
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    • 2018
  • Purpose - Recently, global management in Korea franchise industry is becoming an important keyword. As an important branch market, Chinese market plays a major role not only by making experience of the competitiveness among global brands which offers a foothold to become a top global brand, but also by actualizing an economies of scale in production, sales, etc. Therefore, it is necessary to identify key successful factor influencing customer evaluation and responses of Korean franchise restaurant targeting Chinese consumers in China context. The purpose of this study is to examine the effects for Korean franchise restaurant selection attributes on perceived value, customer satisfaction and customer loyalty in Chinese context with SmartPLS 3 and Artifical Neural Network(ANN). Research design, data, and methodology - For these purposes, the authors developed several hypotheses. A questionnaire survey was conducted on the panel of online survey companies for Chinese consumers who have visited Korean franchise restaurants. A total of 404 data were analyzed using structural equation modeling(SEM) and artifical neural network(ANN) with SPSS 22.0 and SmartPLS 3.0. Result - The findings of this study are as follows: First, the alternative model findings show that facilities & atmosphere, employee service, and menu influenced on utilitarian value, customer satisfaction, and customer loyalty directly. Second, employee service influenced on customer satisfaction. Third, menu influenced on hedonic value. Fourth, brand reputation influenced on utilitarian value. Fifth, hedonic value increase customer satisfaction and customer loyalty. Sixth, hedonic value increase customer loyalty. Seventh, customer increase customer loyalty. And, the ANN analysis shows that utilitarian value is the first most important factor influencing customer satisfaction, followed by hedonic value, facilities & atmosphere, menu and employee service. However, the ANN analysis shows that customer satisfaction is the first most important factor influencing customer loyalty, followed by utilitarian value, hedonic value, brand reputation, menu, and employee service. Conclusions - This study provides practical implications for enhancing customer satisfaction and customer loyalty by applying the ANN technique that complements the limitations of the linear structural relationship analysis using the proposed model and the alternative model. In other words, the SEM-ANN model provides guidelines on how Korean franchise restaurants should formulate facilities & atmosphere, employee service, and menu mix strategies in China. In addition, ANN 's analysis shows that restaurant brand reputation plays a pivotal role in increasing customer loyalty. The fact suggests that Korean franchise companies should establish their domestic brand reputation prior to their entry into overseas markets such as China.

GPT-enabled SNS Sentence writing support system Based on Image Object and Meta Information (이미지 객체 및 메타정보 기반 GPT 활용 SNS 문장 작성 보조 시스템)

  • Dong-Hee Lee;Mikyeong Moon;Bong-Jun, Choi
    • Journal of the Institute of Convergence Signal Processing
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    • v.24 no.3
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    • pp.160-165
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    • 2023
  • In this study, we propose an SNS sentence writing assistance system that utilizes YOLO and GPT to assist users in writing texts with images, such as SNS. We utilize the YOLO model to extract objects from images inserted during writing, and also extract meta-information such as GPS information and creation time information, and use them as prompt values for GPT. To use the YOLO model, we trained it on form image data, and the mAP score of the model is about 0.25 on average. GPT was trained on 1,000 blog text data with the topic of 'restaurant reviews', and the model trained in this study was used to generate sentences with two types of keywords extracted from the images. A survey was conducted to evaluate the practicality of the generated sentences, and a closed-ended survey was conducted to clearly analyze the survey results. There were three evaluation items for the questionnaire by providing the inserted image and keyword sentences. The results showed that the keywords in the images generated meaningful sentences. Through this study, we found that the accuracy of image-based sentence generation depends on the relationship between image keywords and GPT learning contents.