• Title/Summary/Keyword: news data

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Analysis of Weather News using Big Data Analytics Tools R (빅데이터 분석도구 R을 활용한 기상뉴스 데이터분석)

  • Kim, YongSu;Ban, ChaeHoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.448-450
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    • 2016
  • 정보기술과 디지털 경제의 확산으로 대규모의 데이터가 생산되는 정보화시대에서 빅 데이터의 중요성이 강조되고 있으며 다양한 분야에서 이를 응용하고 있다. 빅 데이터 분석도구인 R은 통계 기반의 정보 분석을 가능하게 하는 언어와 환경이다. 본 논문에서는 R을 이용하여 기상뉴스에 나타난 기상관련 빅 데이터를 분석한다. 다양한 뉴스에서 기상 관련 데이터를 수집하고 어떠한 텍스트가 분포되어 있는지 빈도 조사를 수행한다.

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A Video Information Management System for Supporting Caption- and Content-based Searches (주석 및 내용 기반 검색을 지원하는 동영상 정보 관리 시스템)

  • 전미경;김인홍;류시국;전용기;강현석
    • Journal of Korea Multimedia Society
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    • v.2 no.3
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    • pp.231-242
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    • 1999
  • Generally, either caption-based search method or content-based search methods is used to retrieve video information. However, each search method has its limitations. Caption-based search is apt to lose consistency as for user's subjects, and content-based search is hard to extract general means. To enhance efficiency and correctness as for complementing each other, we propose the Integrated Video Data Model(IVDM) which integrates the two search methods, to device the model, we analyze video data and construct the structure of video information hierarchically. IVDM supports caption-based search as assigning meta-data by analyzing thematic-unit in the higher level, and also supports content-based search as extracting feature data by analyzing the content of video data in the lower level. We design Object-Oriented database schema of news video, based-on the IVDM. And we provide 4-type of queries and query processing algorithm to retrieve news video information.

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A Study on the Smart Tourism Awareness through Bigdata Analysis

  • LEE, Song-Yi;LEE, Hwan-Soo
    • The Journal of Industrial Distribution & Business
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    • v.11 no.5
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    • pp.45-52
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    • 2020
  • Purpose: In the 4th industrial revolution, services that incorporate various smart technologies in the tourism sector have begun to gain popularity. Accordingly, academic discussions on smart tourism have also started to become active in various fields. Despite recent research, the definition of smart tourism is still ambiguous, and it is not easy to differentiate its scope or characteristics from traditional tourism concepts. Thus, this study aims to analyze the perception of smart tourism exposed online to identify the current point of smart tourism in Korea and present the research direction for conceptualizing smart tourism suitable for the domestic situation. Research design, data, and methodology: This study analyzes the perception of smart tourism exposed online based on 20,198 news data from portal sites over the past six years. Data on words used with smart tourism were collected from the leading portal sites Naver, Daum, and Google. Text mining techniques were applied to identify the social awareness status of smart tourism. Network analysis was used to visualize the results between words related to smart tourism, and CONCOR analysis was conducted to derive clusters formed by words having similarity. Results: As a result of keyword analysis, the frequency of words related to the development and construction of smart tourism areas was high. The analysis of the centrality of the connection between words showed that the frequency of keywords was similar, and that the words "smartphones" and "China" had relatively high connection centrality. The results of network analysis and CONCOR indicated that words were formed into eight groups including related technologies, promotion, globalization, service introduction, innovation, regional society, activation, and utilization guide. The overall results of data analysis showed that the development of smart tourism cities was a noticeable issue. Conclusions: This study is meaningful in that it clearly reflects the differences in the perception of smart tourism between online and research trends despite various efforts to develop smart tourism in Korea. In addition, this study highlights the need to understand smart tourism concepts and enhance academic discussions. It is expected that such academic discussions will contribute to improving the competitiveness of smart tourism research in Korea.

Crisis Management Analysis of Foot-and-Mouth Disease Using Multi-dimensional Data Cube (다차원 데이터 큐브 모델을 이용한 구제역의 위기 대응 방안 분석)

  • Noh, Byeongjoon;Lee, Jonguk;Park, Daihee;Chung, Yongwha
    • The Journal of the Korea Contents Association
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    • v.17 no.5
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    • pp.565-573
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    • 2017
  • The ex-post evaluation of governmental crisis management is an important issues since it is necessary to prepare for the future disasters and becomes the cornerstone of our success as well. In this paper, we propose a data cube model with data mining techniques for the analysis of governmental crisis management strategies and ripple effects of foot-and-mouth(FMD) disease using the online news articles. Based on the construction of the data cube model, a multidimensional FMD analysis is performed using on line analytical processing operations (OLAP) to assess the temporal perspectives of the spread of the disease with varying levels of abstraction. Furthermore, the proposed analysis model provides useful information that generates the causal relationship between crisis response actions and its social ripple effects of FMD outbreaks by applying association rule mining. We confirmed the feasibility and applicability of the proposed FMD analysis model by implementing and applying an analysis system to FMD outbreaks from July 2010 to December 2011 in South Korea.

A Study on Sentiment Analysis of Media and SNS response to National Policy: focusing on policy of Child allowance, Childbirth grant (국가 정책에 대한 언론과 SNS 반응의 감성 분석 연구 -아동 수당, 출산 장려금 정책을 중심으로-)

  • Yun, Hye Min;Choi, Eun Jung
    • Journal of Digital Convergence
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    • v.17 no.2
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    • pp.195-200
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    • 2019
  • Nowadays as the use of mobile communication devices such as smart phones and tablets and the use of Computer is expanded, data is being collected exponentially on the Internet. In addition, due to the development of SNS, users can freely communicate with each other and share information in various fields, so various opinions are accumulated in the from of big data. Accordingly, big data analysis techniques are being used to find out the difference between the response of the general public and the response of the media. In this paper, we analyzed the public response in SNS about child allowance and childbirth grant and analyzed the response of the media. Therefore we gathered articles and comments of users which were posted on Twitter for a certain period of time and crawling the news articles and applied sentiment analysis. From these data, we compared the opinion of the public posted on SNS with the response of the media expressed in news articles. As a result, we found that there is a different response to some national policy between the public and the media.

Time Window based Cache Replacement Strategy using Popularity and Life of News-Demand Data (NOD(News On Demand) 데이터의 인기도와 생명주기를 이용하는 시간 윈도우에 기반한 캐시 재배치 기법)

  • 최태욱;박성호;김영주;정기동
    • Proceedings of the Korean Information Science Society Conference
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    • 1998.10a
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    • pp.101-103
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    • 1998
  • 뉴스기사를 구성하는 NOD데이터는 VOD(Video on Demand) 데이터와는 달리 미디어의 종류 및 크기, 시간적인 접근 지역성, 사용자와 상호 작용성 등의 차이점을 가질 뿐만 아니라 새로운 뉴스기사가 수시로 생성되고 사용자가 인기도가 높은 기사와 최신의 뉴스기사에 더 많이 접근하는 특성을 가진다. 본 논문에서는 현재 서비스중인 전자신문의 로그파일을 분석하여 NOD 뉴스기사의 인기도가 Zipf분포와 다름을 보이고, 뉴스기사의 생명주기Lifr Cycle)에 따른 접근 확률분포 제시한다. NOD 데이터의 접근 편기성으로 인하여 데이터 캐싱을 통한 NOD 서버의 성능 향상을 기대할 수 있으나 뉴스기사의 생명주기가 짧고 접근시간대별로 사용자 접근형태가 변하는 등의 이유로 단순히 인기도만 고려한 캐싱은 빈번한 데이터 재배치 문제로 인해 높은 캐시 관리비용을 야기한다. 따라서 본 논문에서는 뉴스 기사의 접근 편기성에 나타나는 인기도(popularity)와 생명주기를 조합한 척도를 제안하고 이를 이용한 재배치를 제안한다.

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Company Name Discrimination in Tweets using Topic Signatures Extracted from News Corpus

  • Hong, Beomseok;Kim, Yanggon;Lee, Sang Ho
    • Journal of Computing Science and Engineering
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    • v.10 no.4
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    • pp.128-136
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    • 2016
  • It is impossible for any human being to analyze the more than 500 million tweets that are generated per day. Lexical ambiguities on Twitter make it difficult to retrieve the desired data and relevant topics. Most of the solutions for the word sense disambiguation problem rely on knowledge base systems. Unfortunately, it is expensive and time-consuming to manually create a knowledge base system, resulting in a knowledge acquisition bottleneck. To solve the knowledge-acquisition bottleneck, a topic signature is used to disambiguate words. In this paper, we evaluate the effectiveness of various features of newspapers on the topic signature extraction for word sense discrimination in tweets. Based on our results, topic signatures obtained from a snippet feature exhibit higher accuracy in discriminating company names than those from the article body. We conclude that topic signatures extracted from news articles improve the accuracy of word sense discrimination in the automated analysis of tweets.

A Study on Precaching according to Push Technology for Audio and Video Data in NOD(News On Demand) System (NOD 시스템에서 오디오와 비디오 데이터 Push에 따른 Precaching 연구)

  • 박성호;김광문;송기욱;정기동
    • Proceedings of the Korea Multimedia Society Conference
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    • 1998.04a
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    • pp.323-327
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    • 1998
  • 컴퓨터와 통신망 기술의 발전으로 많은 언론 기관에서 전자신문 서비스를 제공하고 있다. 그러나 현재 서비스되는 전자신문은 텍스트 위주의 정적인 정보를 주고 서비스 하며, 사용자가 필요한 정보를 찾아 다니는 pull 기술을 기반으로 서비스한다. 그리고 사용자 맞춤 기능을 제공하기 못하므로, 불필요한 정보를 사용자에게 전송함으로써 시스템 자원을 낭비하는 단점을 가지고 있다. 본 논문에서는 멀티미디어 데이터를 지원하는 NOD(News On Demand)시스템에서 텍스트 데이터 뿐아니라 오디오/비디오 데이터를 push 하므로써 서버의 load를 분배시키고 사용자에게 실시간성을 제공하는 NOD 분배 서버를 설계하고 프로토타입을 구현하였다. 특히 본 논문에서는 대용량 데이터인 오디오/비디오 데이터를 사용자 시스템으로 Push할 때, 사용자 시스템의 디스크 공간상태 등을 고려하여 실시간성을 유지할 수 있는 적정 Push 량을 시뮬레이션을 통해 측정하였다.

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Learning Algorithms in AI System and Services

  • Jeong, Young-Sik;Park, Jong Hyuk
    • Journal of Information Processing Systems
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    • v.15 no.5
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    • pp.1029-1035
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    • 2019
  • In recent years, artificial intelligence (AI) services have become one of the most essential parts to extend human capabilities in various fields such as face recognition for security, weather prediction, and so on. Various learning algorithms for existing AI services are utilized, such as classification, regression, and deep learning, to increase accuracy and efficiency for humans. Nonetheless, these services face many challenges such as fake news spread on social media, stock selection, and volatility delay in stock prediction systems and inaccurate movie-based recommendation systems. In this paper, various algorithms are presented to mitigate these issues in different systems and services. Convolutional neural network algorithms are used for detecting fake news in Korean language with a Word-Embedded model. It is based on k-clique and data mining and increased accuracy in personalized recommendation-based services stock selection and volatility delay in stock prediction. Other algorithms like multi-level fusion processing address problems of lack of real-time database.

A Study for Conflict in Public Construction Projects Based on Online News (온라인 뉴스 기반 공공건설사업 갈등지수 산정에 관한 기초연구)

  • Baek, Seungwon;Han, Seung Heon;Yun, Sungmin;Lim, Jonglok;Nam, Jihyun
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2021.05a
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    • pp.277-278
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    • 2021
  • Conflict in public construction projects has increased for the last decades. It not only entails enormous social and economic costs but also makes stakeholders suffer from unnecessary expense and time waste. This study defines the the conflict index for public construction projects based on news data, and calculates conflict index for representative past and current public construction projects that has been deepened conflicts at the national level. The result indicates that the major conflict issue of the 2nd Jeju Airport Project are the environment and location whereas that of the Gaduk New Airport Project are the safety, location and necessity. This approach is expected to enable construction project managers to manage conflicts quantitatively based on comparing with past cases.

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