• Title/Summary/Keyword: Content-based Analysis

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An Analysis of the Comparative Importance of Systematic Attributes for Developing an Intelligent Online News Recommendation System: Focusing on the PWYW Payment Model (지능형 온라인 뉴스 추천시스템 개발을 위한 체계적 속성간 상대적 중요성 분석: PWYW 지불모델을 중심으로)

  • Lee, Hyoung-Joo;Chung, Nuree;Yang, Sung-Byung
    • Journal of Intelligence and Information Systems
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    • v.24 no.1
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    • pp.75-100
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    • 2018
  • Mobile devices have become an important channel for news content usage in our daily life. However, online news content readers' resistance to online news monetization is more serious than other digital content businesses, such as webtoons, music sources, videos, and games. Since major portal sites distribute online news content free of charge to increase their traffics, customers have been accustomed to free news content; hence this makes online news providers more difficult to switch their policies on business models (i.e., monetization policy). As a result, most online news providers are highly dependent on the advertising business model, which can lead to increasing number of false, exaggerated, or sensational advertisements inside the news website to maximize their advertising revenue. To reduce this advertising dependencies, many online news providers had attempted to switch their 'free' readers to 'paid' users, but most of them failed. However, recently, some online news media have been successfully applying the Pay-What-You-Want (PWYW) payment model, which allows readers to voluntarily pay fees for their favorite news content. These successful cases shed some lights to the managers of online news content provider regarding that the PWYW model can serve as an alternative business model. In this study, therefore, we collected 379 online news articles from Ohmynews.com that has been successfully employing the PWYW model, and analyzed the comparative importance of systematic attributes of online news content on readers' voluntary payment. More specifically, we derived the six systematic attributes (i.e., Type of Article Title, Image Stimulation, Article Readability, Article Type, Dominant Emotion, and Article-Image Similarity) and three or four levels within each attribute based on previous studies. Then, we conducted content analysis to measure five attributes except Article Readability attribute, measured by Flesch readability score. Before conducting main content analysis, the face reliabilities of chosen attributes were measured by three doctoral level researchers with 37 sample articles, and inter-coder reliabilities of the three coders were verified. Then, the main content analysis was conducted for two months from March 2017 with 379 online news articles. All 379 articles were reviewed by the same three coders, and 65 articles that showed inconsistency among coders were excluded before employing conjoint analysis. Finally, we examined the comparative importance of those six systematic attributes (Study 1), and levels within each of the six attributes (Study 2) through conjoint analysis with 314 online news articles. From the results of conjoint analysis, we found that Article Readability, Article-Image Similarity, and Type of Article Title are the most significant factors affecting online news readers' voluntary payment. First, it can be interpreted that if the level of readability of an online news article is in line with the readers' level of readership, the readers will voluntarily pay more. Second, the similarity between the content of the article and the image within it enables the readers to increase the information acceptance and to transmit the message of the article more effectively. Third, readers expect that the article title would reveal the content of the article, and the expectation influences the understanding and satisfaction of the article. Therefore, it is necessary to write an article with an appropriate readability level, and use images and title well matched with the content to make readers voluntarily pay more. We also examined the comparative importance of levels within each attribute in more details. Based on findings of two studies, two major and nine minor propositions are suggested for future empirical research. This study has academic implications in that it is one of the first studies applying both content analysis and conjoint analysis together to examine readers' voluntary payment behavior, rather than their intention to pay. In addition, online news content creators, providers, and managers could find some practical insights from this research in terms of how they should produce news content to make readers voluntarily pay more for their online news content.

The Content Based Analysis According to the Composition of the Feature Parameters for the Auditory Data (오디오 데이터의 특징 파라메터 구성에 따른 내용기반 분석)

  • 한학용;허강인;김수훈
    • The Journal of the Acoustical Society of Korea
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    • v.21 no.2
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    • pp.182-189
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    • 2002
  • In this paper, we research the content-based analysis and classification according to the composition of the feature parameters pool for the auditory signals to implement the auditory indexing and searching system. Auditory data is classified to the primitive various auditory types. we described the analysis and feature extraction method for the feature parameters available to the auditory data classification. And we compose the feature parameters pool in the indexing group unit, then compare and analysis the auditory data centering around the including level and indexing criterion into the audio categories. Based on this result, we composed the classification procedure and simulate the auditory data classification.

Experimental study on the tensile strength of gravelly soil with different gravel content

  • Ji, Enyue;Chen, Shengshui;Zhu, Jungao;Fu, Zhongzhi
    • Geomechanics and Engineering
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    • v.17 no.3
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    • pp.271-278
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    • 2019
  • In recent years, the crack accidents of earth and rockfill dams occur frequently. It is urgent to study the tensile strength and tensile failure mechanism of the gravelly soil in the core for the anti-crack design of the actual high earth core rockfill dam. Based on the self-developed uniaxial tensile test device, a series of uniaxial tensile test was carried out on gravelly soil with different gravel content. The compaction test shows a good linear relationship between the optimum water content and gravel content, and the relation curve of optimum water content versus maximum dry density can be fitting by two times polynomial. For the gravelly soil under its optimum water content and maximum dry density, as the gravel content increased from 0% to 50%, the tensile strength of specimens decreased from 122.6 kPa to 49.8 kPa linearly. The peak tensile strain and ultimate tensile strain all decrease with the increase of the gravel content. From the analysis of fracture energy, it is proved that the tensile capacity of gravelly soil decreases slightly with the increasing gravel content. In the case that the sample under the maximum dry density and the water content higher than the optimum water content, the comprehensive tensile capacity of the sample is the strongest. The relevant test results can provide support for the anti-crack design of the high earth core rockfill dam.

A Study on the Impact Factors of Contents Diffusion in Youtube using Integrated Content Network Analysis (일반영향요인과 댓글기반 콘텐츠 네트워크 분석을 통합한 유튜브(Youtube)상의 콘텐츠 확산 영향요인 연구)

  • Park, Byung Eun;Lim, Gyoo Gun
    • Journal of Intelligence and Information Systems
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    • v.21 no.3
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    • pp.19-36
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    • 2015
  • Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.

A Machine Learning-based Popularity Prediction Model for YouTube Mukbang Content (머신러닝 기반의 유튜브 먹방 콘텐츠 인기 예측 모델)

  • Beomgeun Seo;Hanjun Lee
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.49-55
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    • 2023
  • In this study, models for predicting the popularity of mukbang content on YouTube were proposed, and factors influencing the popularity of mukbang content were identified through post-analysis. To accomplish this, information on 22,223 pieces of content was collected from top mukbang channels in terms of subscribers using APIs and Pretty Scale. Machine learning algorithms such as Random Forest, XGBoost, and LGBM were used to build models for predicting views and likes. The results of SHAP analysis showed that subscriber count had the most significant impact on view prediction models, while the attractiveness of a creator emerged as the most important variable in the likes prediction model. This confirmed that the precursor factors for content views and likes reactions differ. This study holds academic significance in analyzing a large amount of online content and conducting empirical analysis. It also has practical significance as it informs mukbang creators about viewer content consumption trends and provides guidance for producing high-quality, marketable content.

Keyword-Based Contents Recommendation Web Service (키워드 기반 콘텐츠 추천 웹서비스)

  • Park, Dong-Jin;Kim, Min-Geun;Song, Hyeon-Seop;Yoon, Seok-Min;Kim, Youngjong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.346-348
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    • 2022
  • Media Contents Recommendation Web Service (service name 'mobodra') is a web service that analyzes media types and genre tastes for each user and recommends content accordingly. Users select some of the works randomly provided on the web when signing up for membership and analyze their tastes based on this. Based on this analysis, preferred content for each user is recommended. In this paper, we implement a content recommendation algorithm through item-based collaborative filtering. When the user's activity data or preference is re-examined, the above process is executed again to update the user's taste.

Analysis of Hazardous Heavy Metal in Colored Materials of Playground Facility for Children (어린이 놀이시설의 소재 색상에 따른 유해중금속 분석 연구)

  • Huh, Sun Hae;Weon, Jong-Il
    • Journal of the Korean Society of Safety
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    • v.30 no.2
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    • pp.14-20
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    • 2015
  • The content of hazardous heavy metal of materials used in playground facility for children was investigated using X-ray fluorescence (XRF) and inductively coupled plasma (ICP) analyses, In order to examine the content of hazardous heavy metals according to the material color, four colors, i.e., green, red, yellow and blue, were categorized on the materials used. The highest lead content is observed in the yellow plastic samples. The yellow samples with relatively high lead content show that the chrome content is also high. This can explained that lead chromate, so-called chromium yellow, is normally used as a main pigment to express the yellow color. Therefore, it is concluded that hazardous heavy metal detected in the materials of playground facility for children is due to the pigments used for coloring. Based on above findings, the relationship between the color of materials used in playground facility for children and the content of hazardous heavy metal is discussed.

Nondestructive Sugar Content Measurement in Apple by Nir Spectrum Analysis using Neural Network

  • Lee, S.H.;Noh, S.H.;Kim, W.G.
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1996.06c
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    • pp.325-333
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    • 1996
  • This study was conducted to develop neural networks of predicting the sugar content of fruits based on the optical densities obtained from a spectrophotometer. Pear, apple and peach were used in investigating the feasbility of the developed neural networks as a nondestructive measurement. A spectrophotometer was used to measure the optical densities of test fruits. The neural networks suggested in this study consisted of multi-layers having one hidden layer and one output layer. The correlation coefficients between the predicted and the measured sugar content for most fruits were high. The neural networks using 2nd derivatives of optical density spectrum produced a better results in predicting the sugar content of fruits. This study contributed to develop a method for nondestructively predicting the sugar content of fruits.

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Analysis of the Conceptual Map of Kindergarten Teachers Concerning the Content of Music Instruction (유아음악교육내용에 대한 교사의 개념도 분석)

  • Sim, Seong Kyung;Yi, Hyo Sook;Yim, Sun Ok;Park, Sun Yi;Heo, Eun Ju;Park, Ji Ae
    • Korean Journal of Child Studies
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    • v.24 no.4
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    • pp.71-88
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    • 2003
  • Concept mapping was used to analyze the knowledge of kindergarten teachers about early childhood music instructional content. Data obtained from the 85 subjects was analyzed by Yun's method(1998) based on Novak & Gowin(1984), Morine-Dershimer(1993), and Markhan, Mintzes & Jones(1994). The majority of the teachers perceived the superordinate concepts of early childhood music instructional content to be listening to music, singing, movement, and playing musical instruments. They perceived early childhood music instructional content to be activity rather then knowledge. Listening to music was high in frequency among superordinate concepts and musical attitudes were high among subordinate concepts. Teachers used 285 words in expressing their cognitive maps. There was no effect on cognitive maps by teaching career or level of education.

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Trend analysis of secondary school mathematics teacher certification examination (중등교사 임용시험 수학교과 내용학 문항의 출제 경향 분석)

  • Byun, Ji-Soo;Choi, Byung-Ok
    • Journal for History of Mathematics
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    • v.25 no.3
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    • pp.119-140
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    • 2012
  • This study analyzed the questions related to the content knowledge of mathematics subject for the middle and high school teacher employment examination conducted from the school year of 2009 to 2012 based on the evaluation scope of the mathematics subject content knowledge and evaluation contents which were presented by the Korea Institute for Curriculum and Evaluation(KICE). To achieve the objectives of this study, a total of 105 questions were collected with respect to the questions that appeared on the test over the last 4 years which aimed to evaluate the level of applicants' knowledge related to the contents of mathematics 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 9 subjects. Based on the results, suggestions were presented in relation to the operation of the mathematics curriculum for the department of mathematics 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 9 subjects related to the content knowledge of mathematics. Also, there was a remarkable difference in the ratio of items covered in the test among the evaluation scope by subject. The results of analysis on the evaluation content items suggested that 149 items out of 256 items did not appear in the teacher employment examination for 4 years. Based on such results of analysis, this study discussed the need for readjusting the ratio of items covered in the test of content knowledge related to mathematics or the evaluation scope and evaluation content items.