• Title/Summary/Keyword: Semantic Visualization

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A Study on the User Experience at Unmanned Cafe Using Big Data Analsis: Focus on text mining and semantic network analysis (빅데이터를 활용한 무인카페 소비자 인식에 관한 연구: 텍스트 마이닝과 의미연결망 분석을 중심으로)

  • Seung-Yeop Lee;Byeong-Hyeon Park;Jang-Hyeon Nam
    • Asia-Pacific Journal of Business
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    • v.14 no.3
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    • pp.241-250
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    • 2023
  • Purpose - The purpose of this study was to investigate the perception of 'unmanned cafes' on the network through big data analysis, and to identify the latest trends in rapidly changing consumer perception. Based on this, I would like to suggest that it can be used as basic data for the revitalization of unmanned cafes and differentiated marketing strategies. Design/methodology/approach - This study collected documents containing unmanned cafe keywords for about three years, and the data collected using text mining techniques were analyzed using methods such as keyword frequency analysis, centrality analysis, and keyword network analysis. Findings - First, the top 10 words with a high frequency of appearance were identified in the order of unmanned cafes, unmanned cafes, start-up, operation, coffee, time, coffee machine, franchise, and robot cafes. Second, visualization of the semantic network confirmed that the key keyword "unmanned cafe" was at the center of the keyword cluster. Research implications or Originality - Using big data to collect and analyze keywords with high web visibility, we tried to identify new issues or trends in unmanned cafe recognition, which consists of keywords related to start-ups, mainly deals with topics related to start-ups when unmanned cafes are mentioned on the network.

User Needs Analysis and Information Visualization of National R&D Information Navigation Service for Improving Usability (사용성 향상을 위한 국가R&D정보 내비게이션 서비스의 사용자 니즈 분석과 정보 시각화)

  • Lee, Byeong-Hee;Shon, Kang-Ryul
    • The Journal of the Korea Contents Association
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    • v.13 no.2
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    • pp.512-521
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    • 2013
  • This paper presents the user needs analysis and information visualization for the development of a semantic-based national R&D information navigation service in information service planning phase, which converges and fuses NDSL databases and NTIS databases. To investigate and analyze the user needs for improving usability, we make an improvement plan for R&D information services via a survey targeted at 30 persons, and on-site interviews targeted at 12 persons, almost of who are researchers in industries, universities and government-funded institutes. To design new information visualization service, we propose an interactive national R&D information visualization service, which is provided in navigation type, and prescribe persona and screen prototyping according to the user needs analysis. We design the national R&D information convergence/fusion architecture based on the NDSL databases, including 345,411 academic articles, 620,555 co-authors and 49,958 reports and NTIS databases including 187,466 national R&D projects. We expect that the national R&D information convergence/fusion architecture contributes to R&D information convergence/fusion as a leading model/standard and the interactive navigation-typed information visualization service strengthens usability continuously.

A Novel Cross Channel Self-Attention based Approach for Facial Attribute Editing

  • Xu, Meng;Jin, Rize;Lu, Liangfu;Chung, Tae-Sun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.6
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    • pp.2115-2127
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    • 2021
  • Although significant progress has been made in synthesizing visually realistic face images by Generative Adversarial Networks (GANs), there still lacks effective approaches to provide fine-grained control over the generation process for semantic facial attribute editing. In this work, we propose a novel cross channel self-attention based generative adversarial network (CCA-GAN), which weights the importance of multiple channels of features and archives pixel-level feature alignment and conversion, to reduce the impact on irrelevant attributes while editing the target attributes. Evaluation results show that CCA-GAN outperforms state-of-the-art models on the CelebA dataset, reducing Fréchet Inception Distance (FID) and Kernel Inception Distance (KID) by 15~28% and 25~100%, respectively. Furthermore, visualization of generated samples confirms the effect of disentanglement of the proposed model.

Wrapping based Open Metaverse Platform Architecture (래핑 기반 개방형 메타버스 플랫폼 아키텍처)

  • Park, Je-Ho
    • Journal of the Semiconductor & Display Technology
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    • v.21 no.1
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    • pp.1-4
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    • 2022
  • As computers can express and utilize information in a semantic dimension different from the real world, humans have opened the door to the digital world and have played a pivotal role in the transformation of the human habitual environment. Using metaverse, it can be possible to predict concepts such as virtual currency, artificial intelligence, and virtual reality, which have now become possible for practical systemic visualization. In order to implement the metaverse in the realm of technology, it requires not only a multifaceted discussion on the platform, but also research on an architect that can include the intrinsic complexity of the metaverse. In this paper, we discuss the architecture for an open metaverse platform based on convergence wrapping that can converge various contents into one space, and propose a comprehensive platform design.

Research Trends of Studies Related to the Geological Fieldwork Using Semantic Network Analysis: Focused on the Last 21 Years(2000-2020) (언어 네트워크를 이용한 야외지질답사 관련 연구 동향 분석: 최근 21년(2000~2020년)을 중심으로)

  • Jeong, Dong-Gwon
    • Journal of the Korean Society of Earth Science Education
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    • v.14 no.2
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    • pp.173-192
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    • 2021
  • The purpose of this study is to analyze the previous research on geological fieldwork from 2000 to 2020, examine the tasks that have been focused on, and suggest directions and implications for future geological fieldwork research. The data was conducted for the thesis searched on ScienceON and RISS in relation to geological fieldwork and journals listed in the Korean Citation Index(KCI), and the study title was analyzed using the semantic network analysis. For analysis, the data that had been pre-processed was visualized as a network by semantic network analysis, and frequency and centrality were analyzed. The centrality analysis was based on degree centrality and eigenvector centrality, and all analyzes were performed by dividing the entire study period into four periods: 2000-2005, 2006-2010, 2011-2015, and 2016-2020. As a result, research on geological fieldwork focused more on the development of geological field courses, and in particular, jeju island was actively discussed as a learning site. Also, the study was conducted on students rather than teachers, and among them, high school students showed high frequency and centrality. In addition, it can be seen that studies on the educational effect of geological fieldwork were discussed, either in connection with programs such as STEAM, free-semester program, or indirect geological fieldwork methods such as web, flash panorama, and 3D. This study is meaningful in that it suggests the direction of future research by looking back on the research on geological fieldwork that has been done so far.

A Study on the Direction of Art Policy through Semantic Network Analysis in New Normal Era (뉴노멀(New Normal) 시대 언어네트워크 분석에 의한 예술정책 방향 연구)

  • Kim, Mi Yeon;Kwon, Byeong Woong
    • Korean Association of Arts Management
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    • no.58
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    • pp.153-177
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    • 2021
  • This study attempted to analyze language networks based on the theory of art policy in the New Normal era triggered by COVID-19 and domestic and foreign policy trends. For analysis, data containing key words of "Corona" and "Art" were collected from Google News and Web documents from March to September 2020 to extract 227 refined subject words, and the extracted subject words were analyzed as indicators of frequency and centrality of subject words through the Netminor program. In addition, visualization analysis of semantic networks has been attempted for the analysis of relationships between each topic languages. As a result of the semantic network analysis, the most frequent topic was "Corona," and "Culture and Art," "Art," "Performance," "Online" and "Support" were included in the group with the most frequencies. In the centrality analysis, "Corona" was the most popular, followed by "the era," "after," "post," "art," and "cultural arts," with high frequency, "Corona," "art," and "cultural arts" also dominated most centrality. In particular, the top-level key words in the analysis of frequency and centrality of the topic are 'online' and 'support' and 'policy'. This can be seen as indicating that the rapid rise of non-face-to-face and online content and support policies for the artistic communities are needed due to the dailyization of social distance due to COVID-19.

A Comparative Study on the Social Awareness of Metaverse in Korea and China: Using Big Data Analysis (한국과 중국의 메타버스에 관한 사회적 인식의 비교연구: 빅데이터 분석의 활용 )

  • Ki-youn Kim
    • Journal of Internet Computing and Services
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    • v.24 no.1
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    • pp.71-86
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    • 2023
  • The purpose of this exploratory study is to compare the differences in public perceptual characteristics of Korean and Chinese societies regarding the metaverse using big data analysis. Due to the environmental impact of the COVID-19 pandemic, technological progress, and the expansion of new consumer bases such as generation Z and Alpha, the world's interest in the metaverse is drawing attention, and related academic studies have been also in full swing from 2021. In particular, Korea and China have emerged as major leading countries in the metaverse industry. It is a timely research question to discover the difference in social awareness using big data accumulated in both countries at a time when the amount of mentions on the metaverse has skyrocketed. The analysis technique identifies the importance of key words by analyzing word frequency, N-gram, and TF-IDF of clean data through text mining analysis, and analyzes the density and centrality of semantic networks to determine the strength of connection between words and their semantic relevance. Python 3.9 Anaconda data science platform 3 and Textom 6 versions were used, and UCINET 6.759 analysis and visualization were performed for semantic network analysis and structural CONCOR analysis. As a result, four blocks, each of which are similar word groups, were driven. These blocks represent different perspectives that reflect the types of social perceptions of the metaverse in both countries. Studies on the metaverse are increasing, but studies on comparative research approaches between countries from a cross-cultural aspect have not yet been conducted. At this point, as a preceding study, this study will be able to provide theoretical grounds and meaningful insights to future studies.

An Ontology Editor to describe the semantic association about Web Documents (웹 문서의 의미적 연관성 기술을 위한 온톨로지 에디터)

  • Lee Moo-Hun;Cho Hynu-Kyu;Cho Hyeon-Sung;Cho Sung-Hoon;Jang Chang-Bok;Choi Eui-In
    • The KIPS Transactions:PartD
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    • v.12D no.6 s.102
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    • pp.881-888
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    • 2005
  • As the internet continues to grow, the quantity of information on the Web increases beyond measure. The internet users' abilities and requirements to use information also become varied and complicated. Ontology can describe correct meaning of web resource and relationships between web resources. And it can extract conformable information that a user wants. Accordingly, we need the ontology to represent knowledge. W3C announced OWL(Web Ontology Language), a meaning description technology for such web resources. But, the development of a professional use of tools that can compose and edit effectively is not yet developed adequately. In this paper, we design and implement an Ontology editor which generates and edits OWL documents through intuitional interface, with a OWL parser, a Internal DataModel, and a Serializer.

EcoBlog: 4d Spatial Framework for Ecological Virtual Community (EcoBlog: 생태학적 가상 커뮤니티 구현을 위한 4 차원 공간 프레임워크)

  • Lertlakkhanakul, Jumphon;Bae, Nu-Ri;Choi, Jin-Won;Chun, Chung-Yoon
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.937-944
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    • 2006
  • Although people's anxiety about the environmental problem has been getting higher, they are not provided good quality of knowledge about the environment. Based on this situation, Ecoblog can be a new type of online community to educate the public in ecological knowledge. Especially, Ecoblog can be utilized as a method of "preventive education", and it will contribute to reduce great amounts of environmental budget to restore contaminated environment to previous condition. Ecoblog also utilizes the concept of blog which user can create and append their site with chosen themes. A weblog or a blog is a non-commercial webpage regularly updated through the use of a blogging software which allows the user to "publish" kinds of amalgamations of text and graphics to the page as posts. The technology offered in Ecoblog is utilizing the concept of 4D place and game metaphor in order to provide users the sense of participation, interaction and immersion among them and the growing community. Thus, it requires applying the CAAD technology by implementing semantically well-defined building data model as a core database to create a 4D virtual community. This research focuses on defining a 4d spatial framework suitable for developing an online ecological community. Through our study, the state-of-the-art of online community has been studied at the first step. Second, the scenario of using EcoBlog described with content, visualization and navigation are defined based on the critical features derived at the first step. Finally, a 4d spatial framework composed of semantic building data model, content and rule database is constructed to propose factors that are necessary to establish an ecological virtual community. In conclusion, our framework could enhance the comprehension and interaction between users and virtual buildings in the ecological community by integrating the concept of game design, 4D CAD and semantic data model. Such framework can be applied to any online community for an educational purpose.

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SuperDepthTransfer: Depth Extraction from Image Using Instance-Based Learning with Superpixels

  • Zhu, Yuesheng;Jiang, Yifeng;Huang, Zhuandi;Luo, Guibo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.10
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    • pp.4968-4986
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    • 2017
  • In this paper, we primarily address the difficulty of automatic generation of a plausible depth map from a single image in an unstructured environment. The aim is to extrapolate a depth map with a more correct, rich, and distinct depth order, which is both quantitatively accurate as well as visually pleasing. Our technique, which is fundamentally based on a preexisting DepthTransfer algorithm, transfers depth information at the level of superpixels. This occurs within a framework that replaces a pixel basis with one of instance-based learning. A vital superpixels feature enhancing matching precision is posterior incorporation of predictive semantic labels into the depth extraction procedure. Finally, a modified Cross Bilateral Filter is leveraged to augment the final depth field. For training and evaluation, experiments were conducted using the Make3D Range Image Dataset and vividly demonstrate that this depth estimation method outperforms state-of-the-art methods for the correlation coefficient metric, mean log10 error and root mean squared error, and achieves comparable performance for the average relative error metric in both efficacy and computational efficiency. This approach can be utilized to automatically convert 2D images into stereo for 3D visualization, producing anaglyph images that are visually superior in realism and simultaneously more immersive.