• Title/Summary/Keyword: Content-based Analysis

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An Importance-Performance Analysis on the e-Learning Content Components of Cyber Graduate School (원격대학원 콘텐츠 구성요소에 대한 중요도-수행도 분석: J대학 원격대학원 사례를 중심으로)

  • Lee, Jung Yull
    • Journal of the Korea Convergence Society
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    • v.13 no.2
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    • pp.303-312
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    • 2022
  • In this study, the importance-performance analysis (IPA) of the content components of remote graduate students was conducted. To this end, an online survey of 221 remote graduate students at J University obtained the following results. First, the importance of content components by area was in the order of learning content, interaction, teaching-learning strategy, and evaluation, and the degree of execution was in the order of teaching-learning strategy, interaction, evaluation, and learning content. Second, it was found that there were significant differences between importance and performance in the four areas of content components: learning content, teaching-learning strategy, interaction, and evaluation. The importance-execution analysis (IPA) was conducted in two dimensions: region-specific and item-specific, and the results are as follows. The learning content was found to be the maintenance area, the teaching-learning strategy and interaction were the key improvement areas, and the evaluation area was the overinvestment area. The results of this study can be used as basic data to diagnose the present of remote graduate school content and to gauge what needs to be improved in the future based on it.

Trend Analysis of Secondary School Chemistry Teacher Certification Examination: School Years 2009~2013 (2009~2013학년도 중등교사 임용시험 화학교과 내용학 문항의 출제 경향 분석)

  • Choi, Byungok;Kim, Yongseong
    • Journal of The Korean Association For Science Education
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    • v.33 no.6
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    • pp.1202-1218
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    • 2013
  • This study analyzed questions related to the content knowledge on the subject of chemistry for middle and high school teacher employment examinations conducted from the school years 2009 to 2013 based on the evaluation scope of the chemistry subject content knowledge and evaluation contents that were presented by the Korea Institute for Curriculum and Evaluation (KICE). To achieve the objectives of this study, a total of 140 questions were collected with respect to the questions that appeared on the test over the last 5 years, which aimed to evaluate the level of applicants' knowledge related to the contents of chemistry subject. The ratio of the contents covered in the test was assessed based on the scope of evaluation and the items for evaluation among the 4 subjects. Based on the results, suggestions were presented in relation to the operation of the chemistry curriculum for the Department of Chemistry Education at the college of education or the restructuring of the evaluation scope. There was a significant difference in the ratio of items that appeared on the test among the 4 subjects related to the content knowledge on chemistry. Also, there was a remarkable difference in the ratio of items covered in the test among the evaluation scope by subject. The results of the analysis on the evaluation content items suggested that 41 items out of 122 did not appear in the teacher employment examination for 5 years. Based on such results of analysis, this study discussed the need for readjusting the ratio of items covered in the test on content knowledge related to chemistry or the evaluation scope and evaluation content items.

Modeling Topic Extraction-based Sentiment Analysis Based on User Reviews

  • Kim, Tae-Yeun
    • Journal of Integrative Natural Science
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    • v.14 no.2
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    • pp.35-40
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    • 2021
  • In this paper, we proposed a multi-subject-level sentiment analysis model for user reviews using the Latent Dirichlet Allocation (LDA) method targeting user-generated content (UGC). Data were collected from users' online reviews of hotels in major tourist cities in the world, and 30 hotel-related topics were extracted using the entire user reviews through the LDA technique. Six major hotel-related themes (Cleanliness, Location, Rooms, Service, Sleep Quality, and Value) were selected from the extracted themes, and emotions were evaluated for sentences corresponding to six themes in each user review in the proposed sentiment analysis model. Sentiment was analyzed using a dictionary. In addition, the performance of the proposed sentiment analysis model was evaluated by comparing the emotional values for each subject in the user reviews and the detailed scores evaluated by the user directly for each hotel attribute. As a result of analyzing the values of accuracy and recall of the proposed sentiment analysis model, it was analyzed that the efficiency was high.

Photo Retrieval System using Combination of Smart Sensor and Visual Descriptor (스마트 센서와 시각적 기술자를 결합한 사진 검색 시스템)

  • Lee, Yong-Hwan;Kim, Heung-Jun
    • Journal of the Semiconductor & Display Technology
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    • v.13 no.2
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    • pp.45-52
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    • 2014
  • This paper proposes an efficient photo retrieval system that automatically indexes for searching of relevant images, using a combination of geo-coded information, direction/location of image capture device and content-based visual features. A photo image is labeled with its GPS (Global Positioning System) coordinates and direction of the camera view at the moment of capture, and the label leads to generate a geo-spatial index with three core elements of latitude, longitude and viewing direction. Then, content-based visual features are extracted and combined with the geo-spatial information, for indexing and retrieving the photo images. For user's querying process, the proposed method adopts two steps as a progressive approach, filtering the relevant subset prior to use a content-based ranking function. To evaluate the performance of the proposed scheme, we assess the simulation performance in terms of average precision and F-score, using a natural photo collection. Comparing the proposed approach to retrieve using only visual features, an improvement of 20.8% was observed. The experimental results show that the proposed method exhibited a significant enhancement of around 7.2% in retrieval effectiveness, compared to previous work. These results reveal that a combination of context and content analysis is markedly more efficient and meaningful that using only visual feature for image search.

Associative Interactive play Contents for Infant Imagination

  • Jang, Eun-Jung;Lee, Chankyu;Lim, Chan
    • International journal of advanced smart convergence
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    • v.8 no.1
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    • pp.126-132
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    • 2019
  • Creative thinking appears even before it is expressed in language, and its existence is revealed through emotion, intuition, image and body feeling before logic or linguistics rules work. In this study, Lego is intended to present experimental child interactive content that is applied with a computer vision based on image processing techniques. In the case of infants, the main purpose of this content is the development of hand muscles and the ability to implement imagination. The purpose of the analysis algorithm of the OpenCV library and the image processing using the 'VVVV' that is implemented as a 'Node' in the midst of perceptual changes in image processing technology that are representative of object recognition, and the objective is to use a webcam to film, recognize, derive results that match the analysis and produce interactive content that is completed by the user participating. Research shows what Lego children have made, and children can create things themselves and develop creativity. Furthermore, we expect to be able to infer a diverse and individualistic person's thinking based on more data.

The Effect of Social Media Content Types on User Reactions: Focused on a Case Study of Kew Gardens

  • Park, Yumin;Shin, Yong-Wook
    • Journal of People, Plants, and Environment
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    • v.24 no.2
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    • pp.209-218
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    • 2021
  • Background and objective: Instagram, an image-based social media, is being used as an important outlet for the communication and place marketing of public spaces. The purpose of this paper was to analyze how types of place-based content affect user reactions (Likes and Comments) on Instagram in order to provide basic data on the operation and utilization of social media by public places such as botanical gardens and arboretums. Methods: A total of 850 posts uploaded to the Instagram account of Kew Gardens from November 6, 2014 to July 3, 2020 were classified using 14 subject codes. Multiple regression analysis was performed to evaluate the user's reaction between the dependent variables ("Likes", "Comments") and the independent variables (14 subject codes). Results: The findings showed that user reactions appear to differ depending on the typology of the content, and "Likes" and "Comments" were presented in independent behavioral reactions. In particular, "close-ups of plants (botanic, macro)," "plant colony (botanic, wide)," "place-specific landscape (building, landscape)," "anniversary" and "information" showed positive impacts on both "Likes" and "Comments"which could lead to electronic word-of-mouth and content sharing. Conclusion: Based on these findings, it can be argued that the typology of a botanical garden's content can be used to determine factors that affect the immediate reactions and enhance engagement with users.

A Spam Mail Classification Using Link Structure Analysis (링크구조분석을 이용한 스팸메일 분류)

  • Rhee, Shin-Young;Khil, A-Ra;Kim, Myung-Won
    • Journal of KIISE:Software and Applications
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    • v.34 no.1
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    • pp.30-39
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    • 2007
  • The existing content-based spam mail filtering algorithms have difficulties in filtering spam mails when e-mails contain images but little text. In this thesis we propose an efficient spam mail classification algorithm that utilizes the link structure of e-mails. We compute the number of hyperlinks in an e-mail and the in-link frequencies of the web pages hyperlinked in the e-mail. Using these two features we classify spam mails and legitimate mails based on the decision tree trained for spam mail classification. We also suggest a hybrid system combining three different algorithms by majority voting: the link structure analysis algorithm, a modified link structure analysis algorithm, in which only the host part of the hyperlinked pages of an e-mail is used for link structure analysis, and the content-based method using SVM (support vector machines). The experimental results show that the link structure analysis algorithm slightly outperforms the existing content-based method with the accuracy of 94.8%. Moreover, the hybrid system achieves the accuracy of 97.0%, which is a significant performance improvement over the existing method.

Development of an Analysis Framework for Climate Change Education Programs for Elementary School Students Based on Communities (지역사회 기반 초등학생용 기후변화교육 프로그램 분석틀 개발)

  • Jun-Ho Son;Seonyoung Kim
    • Journal of the Korean Society of Earth Science Education
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    • v.16 no.1
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    • pp.87-102
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    • 2023
  • The purpose of this study is to propose an analytical framework for the essential contents that must be included in a climate change education program for elementary school students based on community issues, which can be used by citizen instructors in the community. To develop the analytical framework, 24 climate environmental education specialists were consulted seven times. The content validity of the final analysis framework was statistically verified using I-CVI and S-CVI coefficients, and the reliability of the expert panel was verified using Fleiss' Kappa coefficient. The final analysis framework consists of three analytical areas (program objectives, program content, program evaluation), seven analysis items, seven analysis indicators, and detailed explanations of the analysis indicators. In particular, by adding detailed explanations for the analysis indicators, the content validity and reliability were increased, and the objective nature of the analysis framework was firmly established. It is expected that the proposed analytical framework for a community-based climate change education program for elementary school students in this study will contribute to the systematic development of the program by citizen instructors.

A Study on the Interest of SNS Users according to New Media Fashion Content Types -Focus on Vogue Korea's Official Instagram- (뉴미디어 패션 콘텐츠 유형에 따른 사용자의 SNS 관심도 연구 -보그 코리아 공식 인스타그램 중심으로-)

  • Lee, Chungsun;Lee, Seunghee
    • Journal of Fashion Business
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    • v.24 no.1
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    • pp.75-87
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    • 2020
  • The purpose of this study is to find trends in new media fashion content by analyzing the fashion content of the official Instagram accounts of domestic fashion magazines that are being transformed by digital media. The framework for these analysis of fashion content type and methods of production is based on one used in an earlier research project. Empirical analysis is conducted on Vogue Korea's official Instagram accounts, using the highest number of major views as the secondary measure of interest. After screening for fashion content in posts on the Vogue Korea account for four months, 291 short video postings were extracted to analyze the number of views the postings received. The results were categorized as 'star', 'show/exhibition', 'product', 'shop', 'fashion film', 'designer', or 'event', included in the data are the number of postings by type and the number of views by post. Based on the characteristics of the creator and the editing, the posts were classified into 'professional production highlight', 'professional production private', 'UCC' or 'GIF' videos, the number of views per post were also collected. The research results show different levels of interest depending on the type of fashion content, and also on the way the videos were produced. The study also investigated how the combination of these two factors affects interest. When producing a new media fashion content, combining a 'star' type post with 'professional production private' video content was most popular. The selection of production method is therefore important even given the same type of content.

Trends and Prospects in the Application of AI Technology for Creative Contents (차세대 콘텐츠를 위한 AI 기술 활용 동향 및 전망)

  • Hong, S.J.;Lee, S.W.;Yoon, M.S.;Park, J.Y.;Lee, S.W.;Kim, A.Y.;Jeong, I.K.
    • Electronics and Telecommunications Trends
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    • v.35 no.5
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    • pp.123-133
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    • 2020
  • With the development of artificial intelligence (AI) and 5G technology, an ecosystem of digital content is gradually becoming intelligent, immersive, and convergent. However, there is not enough ultra-realistic content for the ecosystem. For ultra-realistic content services, creative content technologies using AI are being developed. This paper introduces the trends in and prospects of creative content technologies such as 3D content creation, digital holography, image-based motion recognition, content analysis/understanding/searching, sport AI, and content distribution.