• Title/Summary/Keyword: Topic Clustering.

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Digital Archives of Cultural Archetype Contents: Its Problems and Direction (디지털 아카이브즈의 문제점과 방향 - 문화원형 콘텐츠를 중심으로 -)

  • Hahm, Han-Hee;Park, Soon-Cheol
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.17 no.2
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    • pp.23-42
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    • 2006
  • This is a study of the digital archives of Culturecontent.com where 'Cultural Archetype Contents' are currently in service. One of the major purposes of our study is to point out problems in the current system and eventually propose improvements to the digital archives. The government launched a four-year project for developing the cultural archetype content sources and establishing its related business with the hope of enhancing the nation's competitiveness. More specifically, the project focuses on the production of source materials of cultural archetype contents in the subjects of Korea's history. tradition, everyday life. arts and general geographical books. In addition, through this project, the government also intends to establish a proper distribution system of digitalized culture contents and to control copyright issues. This paper analyzes the digital archives system that stores the culture content data that have been produced from 2002 to 2005 and evaluates the current system's weaknesses and strengths. The summary of our findings is as follows. First. the digital archives system does not contain a semantic search engine and therefore its full function is 1agged. Second, similar data is not classified into the same categories but into the different ones, thereby confusing and inconveniencing users. Users who want to find source materials could be disappointed by the current distributive system. Our paper suggests a better system of digital archives with text mining technology which consists of five significant intelligent process-keyword searches, summarization, clustering, classification and topic tracking. Our paper endeavors to develop the best technical environment for preserving and using culture contents data. With the new digitalized upgraded settings, users of culture contents data will discover a world of new knowledge. The technology we introduce in this paper will lead to the highest achievable digital intelligence through a new framework.

An Analysis of Research Trends in Digital Literacy Education: Implications for Responding to Digital Risks in Science Education (디지털 리터러시 교육 연구 현황 분석 -과학교육에서의 디지털 위험 대응을 위한 함의 도출 -)

  • Gaeun Kim;Wonbin Jang;Minchul Kim
    • Journal of The Korean Association For Science Education
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    • v.44 no.5
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    • pp.433-451
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    • 2024
  • Modern society has become a "digital risk society" with the rapid advancement of digital technologies. The growing use of digital tools in education has led to discussions on managing digital risks that arise in teaching and learning contexts. Among all subjects, science education has experienced significant digital transformation, emphasizing the need for strategies to address digital risks within the subject. This study explores digital literacy education as a possible approach to addressing digital risks in science education. To achieve this, the study analyzes the types of digital risks prevalent in modern society and examines the trends of research on digital risks within the context of digital literacy education. This was done by collecting 415 SSCI articles published over the past decade (2014-2023) with the keyword "Digital Risk" and conducting topic modeling and hierarchical clustering to identify types of digital risks. Additionally, 110 KCI articles published with the keyword "Digital Literacy Education" were collected and classified according to the identified digital risk types. These articles were then compared and analyzed based on publication year, school level, and subject to understand the characteristics of digital risks within science education. The findings are as follows: First, the identified digital risk types include intellectual property infringement, spreading fake news, privacy infringement, cyber financial crimes, gaps in digital literacy, digital technology overdependence, and social structural risks. Second, an analysis of publication trends over the years revealed that discussions on digital risks increased significantly during the COVID-19 pandemic, with research on the digital literacy gap being the most prominent. Third, in terms of school level, digital literacy education addressing digital risks was more actively researched in primary education than in secondary education. Finally, subject-area analysis indicated that science education had the lowest proportion of research on digital risks relative to overall digital literacy studies. In science education, discussions primarily focused on intellectual property infringement, spreading fake news, and gaps in digital literacy. This study emphasizes the importance of addressing digital risks in science education and provides foundational data for further discussions on this topic.

A Mobile Landmarks Guide : Outdoor Augmented Reality based on LOD and Contextual Device (모바일 랜드마크 가이드 : LOD와 문맥적 장치 기반의 실외 증강현실)

  • Zhao, Bi-Cheng;Rosli, Ahmad Nurzid;Jang, Chol-Hee;Lee, Kee-Sung;Jo, Geun-Sik
    • Journal of Intelligence and Information Systems
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    • v.18 no.1
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    • pp.1-21
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    • 2012
  • In recent years, mobile phone has experienced an extremely fast evolution. It is equipped with high-quality color displays, high resolution cameras, and real-time accelerated 3D graphics. In addition, some other features are includes GPS sensor and Digital Compass, etc. This evolution advent significantly helps the application developers to use the power of smart-phones, to create a rich environment that offers a wide range of services and exciting possibilities. To date mobile AR in outdoor research there are many popular location-based AR services, such Layar and Wikitude. These systems have big limitation the AR contents hardly overlaid on the real target. Another research is context-based AR services using image recognition and tracking. The AR contents are precisely overlaid on the real target. But the real-time performance is restricted by the retrieval time and hardly implement in large scale area. In our work, we exploit to combine advantages of location-based AR with context-based AR. The system can easily find out surrounding landmarks first and then do the recognition and tracking with them. The proposed system mainly consists of two major parts-landmark browsing module and annotation module. In landmark browsing module, user can view an augmented virtual information (information media), such as text, picture and video on their smart-phone viewfinder, when they pointing out their smart-phone to a certain building or landmark. For this, landmark recognition technique is applied in this work. SURF point-based features are used in the matching process due to their robustness. To ensure the image retrieval and matching processes is fast enough for real time tracking, we exploit the contextual device (GPS and digital compass) information. This is necessary to select the nearest and pointed orientation landmarks from the database. The queried image is only matched with this selected data. Therefore, the speed for matching will be significantly increased. Secondly is the annotation module. Instead of viewing only the augmented information media, user can create virtual annotation based on linked data. Having to know a full knowledge about the landmark, are not necessary required. They can simply look for the appropriate topic by searching it with a keyword in linked data. With this, it helps the system to find out target URI in order to generate correct AR contents. On the other hand, in order to recognize target landmarks, images of selected building or landmark are captured from different angle and distance. This procedure looks like a similar processing of building a connection between the real building and the virtual information existed in the Linked Open Data. In our experiments, search range in the database is reduced by clustering images into groups according to their coordinates. A Grid-base clustering method and user location information are used to restrict the retrieval range. Comparing the existed research using cluster and GPS information the retrieval time is around 70~80ms. Experiment results show our approach the retrieval time reduces to around 18~20ms in average. Therefore the totally processing time is reduced from 490~540ms to 438~480ms. The performance improvement will be more obvious when the database growing. It demonstrates the proposed system is efficient and robust in many cases.

Methodology for Issue-related R&D Keywords Packaging Using Text Mining (텍스트 마이닝 기반의 이슈 관련 R&D 키워드 패키징 방법론)

  • Hyun, Yoonjin;Shun, William Wong Xiu;Kim, Namgyu
    • Journal of Internet Computing and Services
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    • v.16 no.2
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    • pp.57-66
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    • 2015
  • Considerable research efforts are being directed towards analyzing unstructured data such as text files and log files using commercial and noncommercial analytical tools. In particular, researchers are trying to extract meaningful knowledge through text mining in not only business but also many other areas such as politics, economics, and cultural studies. For instance, several studies have examined national pending issues by analyzing large volumes of text on various social issues. However, it is difficult to provide successful information services that can identify R&D documents on specific national pending issues. While users may specify certain keywords relating to national pending issues, they usually fail to retrieve appropriate R&D information primarily due to discrepancies between these terms and the corresponding terms actually used in the R&D documents. Thus, we need an intermediate logic to overcome these discrepancies, also to identify and package appropriate R&D information on specific national pending issues. To address this requirement, three methodologies are proposed in this study-a hybrid methodology for extracting and integrating keywords pertaining to national pending issues, a methodology for packaging R&D information that corresponds to national pending issues, and a methodology for constructing an associative issue network based on relevant R&D information. Data analysis techniques such as text mining, social network analysis, and association rules mining are utilized for establishing these methodologies. As the experiment result, the keyword enhancement rate by the proposed integration methodology reveals to be about 42.8%. For the second objective, three key analyses were conducted and a number of association rules between national pending issue keywords and R&D keywords were derived. The experiment regarding to the third objective, which is issue clustering based on R&D keywords is still in progress and expected to give tangible results in the future.