• Title/Summary/Keyword: Text data

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Wavelet Based Compression Technique for Efficient Image Transmission in the Wireless Multimedia Sensor Networks (무선 멀티미디어 센서 네트워크에서 효율적인 이미지 전송을 위한 웨이블릿 기반 압축 기법)

  • Kwon, Young-Wan;Lee, Joa-Hyoung;Jung, In-Bum
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.12
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    • pp.2323-2329
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    • 2008
  • Advances in wireless communication and hardware technology have made it possible to manufacture high-performance tiny sensor nodes. More recently, the availability of inexpensive cameras modules that are able to capture multimedia data from the environment has fostered the development of Wireless Multimedia Sensor Networks(WMSNs). WMSN supplements the a advanced technique that senses, transmits, and processes the multimedia contents upon the text based traditional wireless sensor network. Since the amount of data which the multimedia contents have, is significantly larger than that of text based data, multimedia contents require lots of computing power and high network bandwidth. To process the multimedia contents on the wireless sensor node which has very limited computing power and energy, a technique for WMSN should take account of computing resource and efficient transmission. In the paper, we propose a new image compression technique YWCE for efficient compression and transmission of image data in WMSN. YWCE introduces 4 type of technique for motion estimation and compensation based on the Resolution Scalability of Wavelet. Experimental result shows that YWCE has high compression performance with different set of 4 type.

Fashion Consumption Culture in the Post-COVID-19 Era Identified through Big Data Analysis -Focusing on Articles in the Chinese Fashion Network LADYMAX.cn- (포스트 코로나19 시대의 패션 소비문화에 대한 빅데이터 분석 -중국 패션 네트워크인 LADYMAX.cn의 기사를 중심으로-)

  • Bin, Sen;Yum, Haejung;Shim, Soo In
    • Journal of Fashion Business
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    • v.25 no.2
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    • pp.80-97
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    • 2021
  • In this study, the changes in fashion consumption culture in the post-COVID-19 era were examined through big data analysis. Considering that the Chinese market plays a pivotal role in the global fashion industry, big data was collected in the most famous and professional fashion network in China, LADYMAX.cn. As a result of text mining and social network analysis, three major changes were identified as the emerging fashion consumption culture in the post-COVID-19 era. First, as a trend in new media consumption, COVID-19 disease and the development of digital technology tended to encourage consumers to put more importance on the relationship between bloggers and fans than previously. Second, as a trend in reward consumption, consumers tended to be rewarded for their hard work to relieve and comfort their high stress caused by spending a long time worrying about the prolonged COVID-19 situation. Third, as a trend in home-economy consumption, consumers tended to prefer homewear and sportswear more because they were spending longer times at home as the social distancing period was prolonged.

Analysis of Domestic Security Solution Market Trend using Big Data (빅데이터를 활용한 국내 보안솔루션 시장 동향 분석)

  • Park, Sangcheon;Park, Dongsoo
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.5
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    • pp.492-501
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    • 2019
  • To use the system safely in cyberspace, you need to use a security solution that is appropriate for your situation. In order to strengthen cyber security, it is necessary to accurately understand the flow of security from past to present and to prepare for various future threats. In this study, information security words of security/hacking news of Naver News which is reliable by using text mining were collected and analyzed. First, we checked the number of security news articles for the past seven years and analyzed the trends. Second, after confirming the security/hacking word rankings, we identified major concerns each year. Third, we analyzed the word of each security solution to see which security group is interested. Fourth, after separating the title and the body of the security news, security related words were extracted and analyzed. The fifth confirms trends and trends by detailed security solutions. Lastly, annual revenue and security word frequencies were analyzed. Through this big data news analysis, we will conduct an overall awareness survey on security solutions and analyze many unstructured data to analyze current market trends and provide information that can predict the future.

Multimodal Media Content Classification using Keyword Weighting for Recommendation (추천을 위한 키워드 가중치를 이용한 멀티모달 미디어 콘텐츠 분류)

  • Kang, Ji-Soo;Baek, Ji-Won;Chung, Kyungyong
    • Journal of Convergence for Information Technology
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    • v.9 no.5
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    • pp.1-6
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    • 2019
  • As the mobile market expands, a variety of platforms are available to provide multimodal media content. Multimodal media content contains heterogeneous data, accordingly, user requires much time and effort to select preferred content. Therefore, in this paper we propose multimodal media content classification using keyword weighting for recommendation. The proposed method extracts keyword that best represent contents through keyword weighting in text data of multimodal media contents. Based on the extracted data, genre class with subclass are generated and classify appropriate multimodal media contents. In addition, the user's preference evaluation is performed for personalized recommendation, and multimodal content is recommended based on the result of the user's content preference analysis. The performance evaluation verifies that it is superiority of recommendation results through the accuracy and satisfaction. The recommendation accuracy is 74.62% and the satisfaction rate is 69.1%, because it is recommended considering the user's favorite the keyword as well as the genre.

Sentiment analysis of online food product review using ensemble technique (앙상블 기법을 활용한 온라인 음식 상품 리뷰 감성 분석)

  • Kim, Han-Min;Park, Kyungbo
    • Journal of Digital Convergence
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    • v.17 no.4
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    • pp.115-122
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    • 2019
  • In the online marketplace, consumers are exposed to various products and freely express opinions. As consumer product reviews have a important effect on the success of online markets and other consumers, online market needs to accurately analyze the consumers' emotions about their products. Text mining, which is one of the data analysis techniques, can analyze the consumer's reviews on the products and efficiently manage the products. Previous studies have analyzed specific domains and less than 20,000 data, despite the different accuracy of the analysis results depending on the data domain and size. Further, there are few studies on additional factors that can improve the accuracy of analysis. This study analyzed 72,530 review data of food product domain that was not mainly covered in previous studies by using ensemble technique. We also examined the influence of summary review on improving accuracy of analysis. As a result of the study, this study found that Boosting ensemble technique has the highest accuracy of analysis. In addition, the summary review contributed to improving accuracy of the analysis.

A Study on deduction of important factors for new infectious diseases through big data analysis (빅데이터 분석을 통한 신종감염병 중요 요인 도출)

  • Suh, Kyung-Do
    • Journal of Industrial Convergence
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    • v.19 no.3
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    • pp.35-40
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    • 2021
  • This study attempted to derive important factors of emerging infectious diseases by collecting and analyzing text data onto emerging infectious diseases. For this purpose, articles in the Naver News database were directly crawled, pre-processed, and used for data analysis. In addition, additional analysis was performed using Big Kinds. As a result of the priority analysis, the importance was shown in the order of corona, infectious disease, quarantine, vaccine, outbreak, virus, infection, and development. As a result of the proximity centrality analysis, the importance was shown in the order of government, death, and plan, and the analysis result of Big Kinds showed that Covid-19 and the Korea Centers for Disease Control and Prevention were important. Based on the results of this study, it can be said that the government's policy support is needed to raise public awareness of new infectious diseases, prevent disease, and develop vaccines and treatments.

Safety Culture: A Retrospective Analysis of Occupational Health and Safety Mining Reports

  • Tetzlaff, Emily J.;Goggins, Katie A.;Pegoraro, Ann L.;Dorman, Sandra C.;Pakalnis, Vic;Eger, Tammy R.
    • Safety and Health at Work
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    • v.12 no.2
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    • pp.201-208
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    • 2021
  • Background: In the mining industry, various methods of accident analysis have utilized official accident investigations to try and establish broader causation mechanisms. An emerging area of interest is identifying the extent to which cultural influences, such as safety culture, are acting as drivers in the reoccurrence of accidents. Thus, the overall objective of this study was to analyze occupational health and safety (OHS) reports in mining to investigate if/how safety culture has historically been framed in the mining industry, as it relates to accident causation. Methods: Using a computer-assisted qualitative data analysis software, 34 definitions of safety culture were analyzed to highlight key terms. Based on word count and contextual relevance, 26 key terms were captured. Ten OHS reports were then analyzed via an inductive thematic analysis, using the key terms. This analysis provided a concept map representing the 50-year data set and facilitated the use of text framing to highlight safety culture in the selected OHS mining reports. Results: Overall, 954 references and six themes, safety culture, attitude, competence, belief, patterns, and norms, were identified in the data set. Of the 26 key terms originally identified, 24 of them were captured within the text. The results made evident two distinct frames in which to interpret the data: the role of the individual and the role of the organization, in safety culture. Conclusion: Unless efforts are made to understand and alter cultural drivers and share these findings within and across industries, the same accidents are likely to continue to occur.

Social Media Bigdata Analysis Based on Information Security Keyword Using Text Mining (텍스트마이닝을 활용한 정보보호 키워드 기반 소셜미디어 빅데이터 분석)

  • Chung, JinMyeong;Park, YoungHo
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.5
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    • pp.37-48
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    • 2022
  • With development of Digital Technology, social issues are communicated through digital-based platform such as SNS and form public opinion. This study attempted to analyze big data from Twitter, a world-renowned social network service, and find out the public opinion. After collecting Twitter data based on 14 keywords for 1 year in 2021, analyzed the term-frequency and relationship among keyword documents with pearson correlation coefficient using Data-mining Technology. Furthermore, the 6 main topics that on the center of information security field in 2021 were derived through topic modeling using the LDA(Latent Dirichlet Allocation) technique. These results are expected to be used as basic data especially finding key agenda when establishing strategies for the next step related industries or establishing government policies.

A Statistical Analysis of the Causes of Marine Incidents occurring during Berthing (정박 중 발생한 준해양사고 원인에 대한 통계 분석 연구)

  • Roh, Boem-Seok;Kang, Suk-Young
    • Journal of Navigation and Port Research
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    • v.45 no.3
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    • pp.95-101
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    • 2021
  • Marine Incidents based on Heinrich's law are very important in preventing accidents. However, marine Incident data are mainly qualitative and are used to prevent similar accidents through case sharing rather than statistical analysis, which can be confirmed in the marine Incident-related data posted in the Korea Maritime Safety Tribunal. Therefore, this study derived quantitative results by analyzing the causes of marine incidents during berthing using various methods of statistical analysis. To this end, data involving marine incidents from various shipping companies were collected and reclassified for easy analysis. The main keywords were derived via primary analysis using text mining. Only meaningful words were selected via verification by an expert group, and time series and cluster analysis were performed to predict marine incidents that may occur during berthing. Although the role of an expert group was still required during the analysis, it was confirmed that quantitative analysis of marine incidents was feasible, and iused to provide cause and accident prevention information.

Analysis of Agenda-setting Changes in Alpine Agricultural of Uljin-gun Using Text-Mining - Focusing on the Keywords of Mass-media, Blog·Cafe - (텍스트마이닝 기법을 활용한 울진군 금강송 산지농업 의제설정 변화 - 매스미디어와 블로그·카페 키워드를 중심으로 -)

  • Do, Jee-Yoon;Jeong, Myeong-Cheol
    • Journal of the Korean Institute of Rural Architecture
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    • v.24 no.3
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    • pp.47-57
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    • 2022
  • This study attempted to grasp the status and perception of Uljin Geumgangsong by grasping mass media issues and user perception using big data, and to present basic data when constructing monitoring using user perception by examining the establishment relationship of agenda setting from a time-series perspective. The results of collecting and analyzing text data that can identify mass media and visitor awareness are as follows. First, both mass media and visitor keywords were related to the importance of the value and meaning of Uljin Geumgangsong. Second, in the case of the connection network, Geumgang Pine Agriculture was centered, but in the case of difference in perception between mass media and visitors, such results were derived due to the object of interest. Third, in the case of the connection relationship structure, the connection strength was strong because there were many overlapping contents of mass media. Fourth, as a result of the centrality analysis, both mass media and visitor-aware keywords were positively recognized as spaces created and maintained through institutional support, and objective perception could be grasped by finding hidden keywords. Fifth, as a result of time series analysis, it was possible to grasp the flow through the issue keywords that appeared by period, and unlike the past, it was recognized as a place for tourism and travel. Finally, as a result of examining whether the agenda setting is consistent, there is a mass media influence, so it is thought that more diverse and more information and publicity are needed by utilizing it.