• Title/Summary/Keyword: Semantic Visualization

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An Augmented Reality Authoring for Spatiotemporal Table Information (시-공간 도표정보의 증강현실 기반 저작기법)

  • Lee, Seok-Jun;Jung, Soon-Ki
    • 한국HCI학회:학술대회논문집
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    • 2007.02a
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    • pp.636-642
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    • 2007
  • 산업 전반에 적용되는 과학, 공학 분야에는 그 목적에 따라 다양한 형태의 정보가 발생한다. 정보는 이용하는 목적에 따란 가공하는 형식과 표현하는 방식이 달라지며, 정보에 직접적으로 접근하는 사용자에게 어떻게 효과적으로 전달할 것인가 하는 문제는 정보 관리 분야에서 매우 중요한 이슈가 되고 있다. 정보를 사용자에게 보다 명확하게 전달하고, 관리하기 위해서는 원천 데이터를 가공하여 가시화(visualization)하는 과정을 거친다. 정보가시화는 원천데이터를 데이터모델로 정리한 후, 가시화구조(visual structure)로 재정의 한다. 실질적인 가시적 결과는 가시화 구조의 데이터들을 정보모델(information model)상에 반영할 때 이루어진다. 본 논문에서는 건물내부에서 진행되는 행사에 대한 시간-공간적인 정보를 정리한 도표 메타포(table metaphor)를 초기 데이터 모델로 사용하여 가시화 하는 과정을 수행한다. 정보 가시화 과정과 저작 과정은 증강현실(augmented reality) 환경에서 이루어진다. 행사가 진행되는 장소의 건물 구조도(map)상에서 각 장소에서 발생하는 정보들을 재배열하고 정리함으로써, 저작자로 하여금 정보 그 자체에 대한 이해뿐만이 아니라, 해당 정보에 대한 공간적인 이해도 함께 가능하게 한다. 이 같은 몰입형(immersive) 저작시스템은 정보에 대한 공간적인 분배가 필요한 저작에서는 매우 유용하며, 저작하는 환경 자체가 가시화의 결과물이 되므로 정보 저작에 대한 가시적 이해를 최대화 시킬 수 있다.

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Visualized Preference Transition Network Based on Recency and Frequency

  • Masruri, Farid;Tsuji, Hiroshi;Saga, Ryosuke
    • Industrial Engineering and Management Systems
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    • v.10 no.4
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    • pp.238-246
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    • 2011
  • Given a directed graph, we can determine how the user's preference moves from one product item to another. In this graph called "preference transition network", each node represents the product item while its edge pointing to the other nodes represents the transition of user's preference. However, with the large number of items make the network become more complex, unclear and difficult to be interpreted. In order to address this problem, this paper proposes a visualization technique in preference transition analysis based on recency and frequency. By adapting these two elements, the semantic meaning of each item and its transition can be clearly identified by its different types of node size, color and edge style. The experiment in a sales data has shown the results of the proposed approach.

A Study on the Meaning of The First Slam Dunk Based on Text Mining and Semantic Network Analysis

  • Kyung-Won Byun
    • International journal of advanced smart convergence
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    • v.12 no.1
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    • pp.164-172
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    • 2023
  • In this study, we identify the recognition of 'The First Slam Dunk', which is gaining popularity as a sports-based cartoon through big data analysis of social media channels, and provide basic data for the development and development of various contents in the sports industry. Social media channels collected detailed social big data from news provided on Naver and Google sites. Data were collected from January 1, 2023 to February 15, 2023, referring to the release date of 'The First Slam Dunk' in Korea. The collected data were 2,106 Naver news data, and 1,019 Google news data were collected. TF and TF-IDF were analyzed through text mining for these data. Through this, semantic network analysis was conducted for 60 keywords. Big data analysis programs such as Textom and UCINET were used for social big data analysis, and NetDraw was used for visualization. As a result of the study, the keyword with the high frequency in relation to the subject in consideration of TF and TF-IDF appeared 4,079 times as 'The First Slam Dunk' was the keyword with the high frequency among the frequent keywords. Next are 'Slam Dunk', 'Movie', 'Premiere', 'Animation', 'Audience', and 'Box-Office'. Based on these results, 60 high-frequency appearing keywords were extracted. After that, semantic metrics and centrality analysis were conducted. Finally, a total of 6 clusters(competing movie, cartoon, passion, premiere, attention, Box-Office) were formed through CONCOR analysis. Based on this analysis of the semantic network of 'The First Slam Dunk', basic data on the development plan of sports content were provided.

A Life Browser based on Probabilistic and Semantic Networks for Visualization and Retrieval of Everyday-Life (일상생활 시각화와 검색을 위한 확률망과 의미망 기반 라이프 브라우저)

  • Lee, Young-Seol;Hwang, Keum-Sung;Kim, Kyung-Joong;Cho, Sung-Bae
    • Journal of KIISE:Computing Practices and Letters
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    • v.16 no.3
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    • pp.289-300
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    • 2010
  • Recently, diverse information which are location, call history, SMS history, photographs, and video can be collected constantly from mobile devices such as cellular phone, smart phone, and PDA. There are many researchers who study services for searching and abstraction of personal daily life with contextual information in mobile environment. In this paper, we introduce MyLifeBrowser which is developed in our previous work. Also, we explain LPS and correction of GPS coordinates as extensions of previous work and show LPS performance test and evaluate the performance of expanded keywords. MyLifeBrowser which provides searching personal information in mobile device and support of detecting related information according to a fragmentary keyword and common knowledge in ConceptNet. It supports the functionality of searching related locations using Bayesian network that is designed by the authors. In our experiment, we visualize real data through MyLifeBrowser and show the feasibility of LPS server and expanded keywords using both Bayesian network and ConceptNet.

Analysis of Deep Learning-Based Pedestrian Environment Assessment Factors Using Urban Street View Images (도시 스트리트뷰 영상을 이용한 딥러닝 기반 보행환경 평가 요소 분석)

  • Ji-Yeon Hwang;Cheol-Ung Choi;Kwang-Woo Nam;Chang-Woo Lee
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.6
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    • pp.45-52
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    • 2023
  • Recently, as the importance of walking in daily life has been emphasized, projects to guarantee walking rights and create a pedestrian environment are being promoted throughout the region. In previous studies, a pedestrian environment assessment was conducted using Jeonju-si road images, and an image comparison pair data set was constructed. However, data sets expressed in numbers have difficulty in generalizing the judgment criteria of pedestrian environment assessors or visually identifying the pedestrian environment preferred by pedestrians. Therefore, this study proposes a method to interpret the results of the pedestrian environment assessment through data visualization by building a web application. According to the semantic segmentation result of analyzing the walking environment components that affect pedestrian environment assessors, it was confirmed that pedestrians did not prefer environments with a lot of "earth" and "grass," and preferred environments with "signboards" and "sidewalks." The proposed study is expected to identify and analyze the results randomly selected by participants in the future pedestrian environment evaluation, and believed that more improved accuracy can be obtained by pre-processing the data purification process.

Converting Triangulated 3D Indoor Mesh Data to OGC IndooGML (삼각분할된 3차원 실내공간데이터를 OGC IndoorGML로 변환하는 방법)

  • Li, Ki-Joune;Kim, Dong Min
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.36 no.6
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    • pp.499-505
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    • 2018
  • Most of 3D indoor spatial data recently constructed by many projects merely focus on the visualization rather than geospatial information applications. The 3D indoor data for visualization in 3DS or COLLADA format are based on triangular mesh representation. In order to implement meaningful applications, we need however more meaningful information in 3D indoor spatial data than visualization data in triangular meshes. For this reason, an OGC (Open Geospatial Consortium) standard, called IndoorGML(Indoor Geographic Markup Language) was published to meet the requirements on 3D indoor spatial data for several geospatial applications for indoor space more than simple visualization. It means that it becomes a critical functional requirement to convert triangular mesh representation in 3DS or COLLADA to IndoorGML. In this paper we propose a framework of the conversion, which consists of geometric, topological, and semantic construction of data from triangular meshes. An experiment carried out to validate the proposed framework is also presented in the paper.

Semantic Network Analysis of Science Gifted Middle School Students' Understanding of Fact, Hypothesis, Theory, Law, and Scientificness (언어 네트워크 분석법을 통한 중학교 과학영재들의 사실, 가설, 이론, 법칙과 과학적인 것의 의미에 대한 인식 조사)

  • Lee, Jun-Ki;Ha, Minsu
    • Journal of The Korean Association For Science Education
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    • v.32 no.5
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    • pp.823-840
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    • 2012
  • The importance of teaching the nature of science (NOS) has been emphasized in the science curriculum, especially in the science curriculum for science-gifted students. Nevertheless, few studies concerning the structure and formation of students' mental model on NOS have been carried out. This study aimed to explore science-gifted students' understanding of 'fact', 'hypothesis', 'theory', 'law', and 'scientificness' by utilizing semantic network analysis. One hundred ten science-gifted middle school students who were selected by a national university participated in this study. We collected students' written responses of five items and analyzed them by the semantic network analysis(SNA) method. As a result, the core ideas of students' understanding of 'fact' were proof and reality, of 'hypothesis' were tentativeness and uncertainty, of 'theory' was proven hypothesis by experimentation, of 'law' were absoluteness and authority, and of 'scientificness' were factual evidence, verifiability, accurate and logical theoretical framework. The result of integrated semantic network illustrated that the viewpoint of science-gifted students were similar to absolutism and logical positivism (empiricism). Methodologically, this study showed that the semantic network analysis method was an useful tool for visualization of students' mental model of scientific conceptions including NOS.

APPLICATION OF HIGH RESOLUTION SATELLITE IMAGERY ON X3D-BASED SEMANTIC WEB USING SMART GRAPHICS

  • Kim, Hak-Hoon;Lee, Kiwon
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.586-589
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    • 2006
  • High resolution satellite imagery is regarded as one of the important data sets to engineering application, as well as conventional scientific application. However, despite this general view, there are a few target applications using this information. In this study, the possibility for the future wide uses in associated with smart graphics of this information is investigated. The concept of smart graphics can be termed intelligent graphics with XML-based structure and knowledge related to semantic web, which is a useful component for the data dissemination framework model in a multi-layered web-based application. In the first step in this study, high resolution imagery is transformed to GML (Geographic Markup Language)-based structure with attribute schema and geo-references. In the second, this information is linked with GIS data sets, and this fused data set is represented in the X3D (eXtensible 3D), ISO-based web 3D graphic standard, with styling attributes, in the next stop. The main advantages of this approach using GML and X3D are the flourished representations of a source data according to user/clients’ needs and structured 3D visualization linked with other XML-based application. As for the demonstration of this scheme, 3D urban modelling case with actual data sets is presented.

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A Comparison of Starbucks between South Korea and U.S.A. through Big Data Analysis (빅데이터 분석을 통한 한국과 미국의 스타벅스 비교 분석)

  • Jo, Ara;Kim, Hak-Seon
    • Culinary science and hospitality research
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    • v.23 no.8
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    • pp.195-205
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    • 2017
  • The purpose of this study was to compare the Starbucks in South Korea with Starbucks in U.S.A through the semantic network analysis of big data by collecting online data with SCTM(Smart Crawling & Text Mining) program which was developed by big data research institute at Kyungsung University, a data collecting and processing program. The data collection period was from January 1st 2014 to December 7th 2017, and packaged Netdraw along with UCINET 6.0 were utilized for data analysis and visualization. After performing CONCOR(convergence of iterated correlation) analysis and centrality analysis, this study illustrated the current characteristics of Starbucks for Korea and U.S.A reflected by the social network and the differences between Korea and U.S.A. Since the Starbucks was greatly developed, especially in Korea. this study also was supposed to provide significant and social-network oriented suggestions for Starbucks USA, Starbucks Korea and also the whole coffee industry. Also this study revealed that big data analytics can generate new insights into variables that have been extensively studied in existing hospitality literature. In addition, implications for theory and practice as well as directions for future research are discussed.

A Study on Changes in Korean Image of Foreign Tourists Using Big Data - Post COVID-19 -

  • Yoo, Kyoung-Mi;Choi, Youn-Hee;Ryu, Gi-Hwan
    • International Journal of Internet, Broadcasting and Communication
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    • v.13 no.4
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    • pp.72-78
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    • 2021
  • Currently, the Korean wave is not limited to popular culture, but has a significant impact not only on Korea's national image but also on the improvement of Korean companies' products and image of Korea. In this study, using Textom to confirm the change in foreign tourists' image of Korea, the data collection period was 1 year of 2020, when COVID 19 occurred, as a collection period for "Korea and foreigner" and related key words, each Hallyu content, and ranked in the top 80 keywords were derived. Centrality analysis for semantic network visualization was performed using UCINET6, and through CONCOR analysis, 7 groups 'K-Quarantine ', 'K-Drama', 'K-Movie', 'K-Beauty', 'K-Shopping', It was clustered into 'K-Tech' and 'K-Pop'. As a result of the analysis, the image of Korea abroad generally recognized the Korean Wave as cultural content, but after the outbreak of COVID 19, it is judged that it has been recognized as a country with a successful case of K-Quarantine.