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검색결과 114건 처리시간 0.032초

비디오 샷 검증 시스템 (A Video Shot Verification System)

  • 정지문
    • 디지털융복합연구
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    • 제7권2호
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    • pp.93-102
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    • 2009
  • Since video is composed of unstructured data with massive storage and linear forms, it is essential to conduct various research studies to provide the required contents for users who are accustomed to dealing with standardized data such as documents and images. Previous studies have shown the occurrence of undetected and false detected shots. This thesis suggested shot verification and video retrieval system using visual rhythm to reduce these kinds of errors. First, the system suggested in this paper is designed to detect the parts easily and quickly, which are assumed as shot boundaries, just by changing the visual rhythm without playing the image. Therefore, this enables to delete the false detected shot and to generate the unidentified shot and key frame. The following are the summaries of the research results of this study. Second, during the retrieving process, a thumbnail and keyword method of inquiry is possible and the user is able to put some more priorities on one part than the other between the color and shape. As a result, the corresponding shot or scene is displayed. However, in the case of not finding the preferred shot, the key picture frame of similar shot is supplied and can be used in the further inquiry of the next scene.

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동시링크를 이용한 웹 문서 클러스터링 실험 (Clustering of Web Document Exploiting with the Co-link in Hypertext)

  • 김영기;이원희;권혁철
    • 한국도서관정보학회지
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    • 제34권2호
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    • pp.233-253
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    • 2003
  • 인간은 지식의 조직을 통해 세계를 이해한다. 정보검색분야에서 연구되고 있는 정보의 조직화에는 분류와 클러스터링이라는 두 가지 유형이 있다. 분류는 미리 정의된 범주에 각 항목을 배정하는 행위인 반면, 클러스터링은 유사하거나 관련된 항목을 집단화함으로써 정보를 조직한다. 인터넷 정보자원의 조직은 웹 문서에 출현하는 단어들에서 키워드를 추출하여 역파일을 작성함으로써 검색에 활용하는 것이 일반적인 방법이다. 그러나 키워드의 출현 위치나 단어빈도를 통한 문서유사도 기법은 사용된 언어가 다르거나 대부분이 앵커텍스트만으로 구성되어 있는 대문페이지처럼 적용하기 어려운 경우가 많다. 이 연구는 계량정보학적 분석 기법 중에서 동시인용 기법을 웹 문서의 하이퍼링크에 적용하여, 웹 문서의 클러스터링 가능성을 실험한다.

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일본 조경관련 분야의 성능규정화 대비방안 (Preparatory Applications for Performance-based Regulatory System in Japanese Landscape Architecture Related Fields)

  • 김민수
    • 한국조경학회지
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    • 제35권5호
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    • pp.37-45
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    • 2007
  • WTO/TBT requires that, for technical regulations affecting trade, technical regulatory requirements must be specified where possible in terms of performance rather than design or descriptive characteristics. The movement which made "performance" a keyword in landscape architecture was activated in Japan, one of the leading counties in performance-based regulatory system(PBRS). The Japanese recent movement of systematization activity on performance-based standards and specifications was reviewed and operational applications for performance-based regulatory system in South Korea are summarized as follows: 1. The establishment of performance standards that can be properly evaluated by assessment indicators is necessary in cases when quantitative evaluation is difficult. 2. As a preparation for PBRS, a brief procurement system by technical proposal for the landscape design and construction is necessary. 3. As a preparation for PBRS, activation of an environmental performance evaluation on experimental construction is necessary. 4. As a preparation for PBRS, a certification system of environmental performance on various landscape construction methods is necessary. 5. The Private Finance Initiative Project is the most similar to PBRS therefore, activation of the Private Finance Initiative Project is necessary in landscape architecture projects for park rehabilitation.

Performance Evaluations of Text Ranking Algorithms

  • Kim, Myung-Hwi;Jang, Beakcheol
    • 한국컴퓨터정보학회논문지
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    • 제25권2호
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    • pp.123-131
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    • 2020
  • 텍스트 순위 알고리즘은 키워드 추출을 위한 대표적인 방법이며 그 중요성이 강조되고 있다. 본 논문에서는 텍스트 랭킹 알고리즘에서 대표적으로 사용되는 TF-IDF, SMART, INQUERY, CCA 알고리즘이 적용된 최근 연구와 실험해비교한다. 먼저, 각 알고리즘을 설명한 후 뉴스와 트위터 데이터를 기반으로 알고리즘의 성능을 분석한다. 실험 결과에 따르면 네 가지 알고리즘 모두 뉴스 데이터에서 특정 단어의 추출 성능이 좋다는 것을 알 수 있다. 그러나 Twitter의 경우 CCA는 특정 단어를 추출하는 최고의 성능을 가지며 INQUERY는 가장 낮은 성능을 보여준다. 또한 6 가지 비교 메트릭을 통해 알고리즘의 정확성을 분석한다. 실험 결과 CCA가 뉴스 데이터에서 최고의 정확도를 보여주고, 트위터의 경우 TF-IDF와 CCA는 비슷한 성능을 보이며 높은 정확도를 보인다.

토픽 식별성 향상을 위한 키워드 재구성 기법 (Keyword Reorganization Techniques for Improving the Identifiability of Topics)

  • 윤여일;김남규
    • 한국IT서비스학회지
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    • 제18권4호
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    • pp.135-149
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    • 2019
  • Recently, there are many researches for extracting meaningful information from large amount of text data. Among various applications to extract information from text, topic modeling which express latent topics as a group of keywords is mainly used. Topic modeling presents several topic keywords by term/topic weight and the quality of those keywords are usually evaluated through coherence which implies the similarity of those keywords. However, the topic quality evaluation method based only on the similarity of keywords has its limitations because it is difficult to describe the content of a topic accurately enough with just a set of similar words. In this research, therefore, we propose topic keywords reorganizing method to improve the identifiability of topics. To reorganize topic keywords, each document first needs to be labeled with one representative topic which can be extracted from traditional topic modeling. After that, classification rules for classifying each document into a corresponding label are generated, and new topic keywords are extracted based on the classification rules. To evaluated the performance our method, we performed an experiment on 1,000 news articles. From the experiment, we confirmed that the keywords extracted from our proposed method have better identifiability than traditional topic keywords.

변형된 한글 금칙어에 대한 실시간 필터링 시스템 (Realtime Word Filtering System against Variations of Censored Words in Korean)

  • 김찬우;성미영
    • 한국멀티미디어학회논문지
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    • 제22권6호
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    • pp.695-705
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    • 2019
  • The level of psychological damage caused by verbal abuse among cyberbully victims is very serious. It is going to introduce a system that determines the level of sanctions against chatting in real time using the automatic prohibited words filtering based on artificial neural network. In this paper, we propose a keyword filtering method that detects the modified prohibited words and determines whether the corresponding chat should be sanctioned in real time, and a real-time chatting screening system using it. The accuracy of filtering through machine learning was improved by processing data in advance through coding techniques that express consonants and vowels of similar pronunciation at close distances. After comparing and analyzing Mahalanobis-based clustering algorithms and artificial neural network-based algorithms, algorithms that utilize artificial neural networks showed high performance. If it is applied to Internet chatting, comments or online games, it is expected that it will be able to filter more effectively than the existing filtering method and that this will ease communication inconvenience due to existing indiscriminate filtering methods.

How do People Understand and Express "Smart City?": Analysis of Transition in Smart-city Keywords through Semantic Network Analysis of SNS Big Data between 2011 and 2020

  • Kim, Seong-A;Kim, Heungsoon
    • Architectural research
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    • 제24권2호
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    • pp.41-52
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    • 2022
  • The purpose of this study is to grasp the understanding of smart cities and to review whether the common perception of smart cities, as people understand it, is changing over time. This study analyzes keywords related to smart cities used in social network services (SNSs) in 2011, 2016, and 2020 respectively through semantic network analysis. Smart city discussions appearing on SNS in 2011 mainly focused on technology, and the results of 2016 were generally similar to those of 2011. We can also find policy or business-oriented characteristics in emerging countries in 2020. We highlight that all the results of 2011, 2016, and 2020 have some correlation with each other through QAP(Quadratic Assignment Procedure) correlation analysis, and among them, the correlation between 2011 and 2016 is analyzed the most. The results of the frequency analysis, centrality analysis, and CONCOR(CONvergence of interaction CORrelation) analysis support these results. The results of this study help establish policies that reflect the needs and opinions of citizens in planning smart cities by identifying trends and paradigm transitions expressed by people in SNS. Furthermore, it is expected to help emerging countries by enhancing the understanding of the essence and trend of smart cities and to contribute by suggesting the direction of more sustainable technology development in future smart city policies for leading countries.

소셜 미디어 빅데이터를 활용한 호캉스(hocance) 현상 분석 (An Analysis of the Hocance Phenomenon using Social Media Big Data)

  • 최홍열;박은경;남장현
    • 아태비즈니스연구
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    • 제12권2호
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    • pp.161-174
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    • 2021
  • Purpose - The purpose of this study was to examine the recent popular consumption trend, the hocance phenomenon, using social media big data. The study intended to present practical directions and marketing measures for the recovery and growth of the hotel industry after COVID-19 pandemic. Design/methodology/approach - Big data analysis has been used in various fields, and in this study, it was used to understand the hocance phenomenon. For three years from January 1, 2018 to December 31, 2020, we collected text data including the keyword 'hocance' from the blog and cafe of NAVER and Daum. TEXTOM and UCINET 6 were used to collect and analyze the data. Findings - According to the results of analysis, the words such as 'hocance', 'hotel', 'Seoul', 'travel', 'swimming pool', 'Incheon', 'breakfast', 'child' and 'friend' were identified with high frequency. The results of CONCOR analysis showed similar results in all three years. It has been confirmed that 'swimming pool', 'breakfast', 'child' and 'friend' are important when deciding on the hocance package. Research implications or Originality - The study was differentiated in that it used social media big data instead of traditional research methods. Furthermore, it reflected social phenomena as a consumption trend so there was practical value in establishing marketing strategies for the tourism and hotel industry.

대한민국 정권별 아동복지정책 관련 뉴스 기사 분석: K-평균 군집 분석 (Analysis of News Articles on Child Welfare Policies in South Korea: K-Means Clustering)

  • 김은주;김성광;박빛나
    • 동서간호학연구지
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    • 제29권2호
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    • pp.185-195
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    • 2023
  • Purpose: The purpose of this study is to analyze changes of child welfare policies and provide insights based on the collection and classification of newspaper articles. Methods: Articles related to child welfare policies were collected from 1990, during the Kim, Young-sam administration, to May 9, 2022, under the Moon, Jae-in administration. K-Means clustering and keyword Term Frequency-Inverse Document Frequency analysis were utilized to cluster and analyze newspaper articles with similar themes. Results: The administrations of Kim, Young-sam, Kim, Dae-jung, Roh, Moo-hyun, and Park, Geun-hye were classified into two clusters, and the Lee, Myung-bak and Moon, Jae-in administrations were classified into three clusters. Conclusion: South Korea's child welfare policies have focused on ensuring the safety and healthy development of children through diverse policies initiatives over the years. However, challenges related to child protection and child abuse persist. This requires additional resources and budget allocation. It is important to establish a comprehensive support system for children and families, including comprehensive nursing support.

빅데이터를 이용한 비건 패션 쟁점의 분석 -한국, 중국, 미국을 중심으로- (Perception and Trend Differences between Korea, China, and the US on Vegan Fashion -Using Big Data Analytics-)

  • 정지운;윤소정
    • 한국의류학회지
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    • 제47권5호
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    • pp.804-821
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    • 2023
  • This study examines current trends and perceptions of veganism and vegan fashion in Korea, China, and the United States. Using big data tools Textom and Ucinet, we conducted cluster analysis between keywords. Further, frequency analysis using keyword extraction and CONCOR analysis obtained the following results. First, the nations' perceptions of veganism and vegan fashion differ significantly. Korea and the United States generally share a similar understanding of vegan fashion. Second, the industrial structures, such as products and businesses, impacted how Korea perceived veganism. Third, owing to its ongoing sociopolitical tensions, the United States views veganism as an ethical consumption method that ties into activism. In contrast, China views veganism as a healthy diet rather than a lifestyle and associates it with Buddhist vegetarianism. This perception is because of their religious history and culinary culture. Fundamentally, this study is meaningful for using big data to extract keywords related to vegan fashion in Korea, China, and the United States. This study deepens our understanding of vegan fashion by comparing perceptions across nations.