• Title/Summary/Keyword: market information quality

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Comparative Analysis of National Policies for Open Data Government Ecosystem (공공데이터 생태계 조성을 위한 주요 국가별 정책에 관한 비교 분석)

  • Song, Seokhyun;Lee, Jai Yong
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.41 no.1
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    • pp.128-139
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    • 2018
  • As The Fourth Industrial Revolution and Intelligent Information Age came into full-scale, the policy of open government data has become a hot topic for each country. The United States, the United Kingdom, and other countries are shifting policy direction to "creating value" of open government data. Also, in the age of the digital economy where the data market is soaring, open government data is gradually being recognized as a new raw material for new business and start-ups. In addition, Korea ranked first in the OECD open government data evaluation twice in a row, and was highly evaluated in the international evaluation. However, domestic firms are still lacking in qualitative openness of government data, data is dispersed among institutions, lack of public-private data linkage, and development of app-oriented development. This study attempts to analyze major national policies for the creation of a data ecosystem that considers data lifecycle, from production to storage, distribution and utilization of data. First, the target countries were the leading public data countries among the OGP member countries, the USA, the UK, Australia and Canada. The results of this study are as follows. As a result of analyzing the results and comparing Korea's policies, it was concluded that most of Korea is superior in open government data policy. However, improvement of data quality, development of open data portal as an open platform, support for finding various users including apps and web development companies, and cultivation of open government data utilizing personnel are analyzed as policy issues. In addition, the direction of policy for the balanced ecosystem of Korea is presented together.

Development of e-Commerce System Based on Social Network Service (SNS 기반 e커머스 시스템 개발)

  • Lee, Tong-Queue
    • Journal of Digital Convergence
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    • v.16 no.1
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    • pp.153-158
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    • 2018
  • Fundamental problems of e-commerce are exaggerated advertising of products, lack of trust in products or suppliers, and false reviews. As a solution, I have merged the concept of trust service embedded in social network service(SNS) with commercial domain to develop a new type of service called "Reliable SNS Commerce Service". The contents developed in this paper are as follows: first, online community functions for users to provide services; second, commerce functions; and third, functions for linking SNS and commerce. Through the reliability information presented in this paper, the seller provides more reliable and objective purchase information to the buyer about the sales items, thereby contributing to the sales by increasing the probability of the actual purchase. The buyer can purchase the higher-quality products with confidence. The service providers can gain the reputation as a reliable site for purchasing members. In conclusion, this paper provides a positive effect to all the participants, which will contribute to the development of a new commerce market and activation of electronic commerce.

An analysis on the influence of the China government's software support policy on the revenue of software export (중국 소프트웨어 지원정책이 중국 소프트웨어 수출액에 미치는 영향 분석)

  • Choi, JeongHo;Zhang, YongAn
    • Journal of the Korean Data and Information Science Society
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    • v.27 no.4
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    • pp.875-886
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    • 2016
  • In this study, we investigate an influence of the China government's software support policy on the revenue of software export. In the analysis in the areas of technology development, manpower development, quality control and marketing reinforcement from 2008 to 2014, it has been found that the amounts of the policy influence and annual revenue of software export increase simultaneously, proving that the China government's support policy has a close relationship with the software export revenue. However, the annual ratio of the software export revenue to the gross software production revenue has decreased over the period, which indicates that the growth of software industry in China has been mainly driven by domestic market.

A study of Polarization Modulator to Single-cell type in Polarized Glasses 3D Display System Using Binocular Parallax

  • Kong, Kyung-Bae;Kwon, Jung-Jang
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.11
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    • pp.71-78
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    • 2019
  • Most 3D displays that are currently in the market adopt the binocular disparity method creating a different image for the left and right eye for a 3 dimensional effect. However, commercialized 3D image output devices lack in performance making it uncomfortable for the viewer and restrict the viewer to certain positions. In this paper, we propose a single-cell polarized lens type stereoscopic system which has a smaller viewing angle and reduced crosstalk, with improved light penetration compared to existing double-cell structures; and analyzed the single-cell polarized lens type stereoscopic system properties, and conducted an effect analysis of performance improvement compared to the dual-cell type. Results showed that the single-cell type had a 25% improved performance, and the 3D crosstalk index which is an important index for quality characteristics of stereoscopic systems, increased over about 37%, compared to the dual-cell type.

Strategic Analysis of the Multilateral Bargaining for the Distribution Channels with Different Transaction Costs (거래비용이 상이한 복수의 유통채널에 대한 다자간 협상전략에 관한 연구)

  • Cho, Hyung-Rae;Rhee, Minho
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.38 no.4
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    • pp.80-87
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    • 2015
  • The proliferation of the Internet and communication technologies and applications, besides the conventional retailers, has led to a new form of distribution channel, namely home sopping through the telephone, TV, catalog or the Internet. The conventional and new distribution channels have different transaction costs perceived by the consumers in the following perspectives: the accessibility to the product information, the traffic cost and the opportunity cost for the time to visit the store, the possibility of 'touch and feel' to test the quality of the product, the delivery time and the concern for the security for the personal information. Difference in the transaction costs between the distribution channels results in the different selling prices even for the same product. Moreover, distribution channels with different selling prices necessarily result in different business surpluses. In this paper, we study the multilateral bargaining strategy of a manufacturer who sells a product through multiple distribution channels with different transaction costs. We first derive the Nash equilibrium solutions for both simultaneous and sequential bargaining games. The numerical analyses for the Nash equilibrium solutions show that the optimal bargaining strategy of the manufacturer heavily depends not only on the degree of competition between the distribution channels but on the difference of the business surpluses of the distribution channels. First, it is shown that there can be four types of locally optimal bargaining strategies if we assume the market powers of the manufacturer over the distribution channels can be different. It is also shown that, among the four local optimal bargaining strategies, simultaneous bargaining with the distribution channels is the most preferred bargaining strategy for the manufacturer.

Customer Attitude to Artificial Intelligence Features: Exploratory Study on Customer Reviews of AI Speakers (인공지능 속성에 대한 고객 태도 변화: AI 스피커 고객 리뷰 분석을 통한 탐색적 연구)

  • Lee, Hong Joo
    • Knowledge Management Research
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    • v.20 no.2
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    • pp.25-42
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    • 2019
  • AI speakers which are wireless speakers with smart features have released from many manufacturers and adopted by many customers. Though smart features including voice recognition, controlling connected devices and providing information are embedded in many mobile phones, AI speakers are sitting in home and has a role of the central en-tertainment and information provider. Many surveys have investigated the important factors to adopt AI speakers and influ-encing factors on satisfaction. Though most surveys on AI speakers are cross sectional, we can track customer attitude toward AI speakers longitudinally by analyzing customer reviews on AI speakers. However, there is not much research on the change of customer attitude toward AI speaker. Therefore, in this study, we try to grasp how the attitude of AI speaker changes with time by applying text mining-based analysis. We collected the customer reviews on Amazon Echo which has the highest share of AI speakers in the global market from Amazon.com. Since Amazon Echo already have two generations, we can analyze the characteristics of reviews and compare the attitude ac-cording to the adoption time. We identified all sub topics of customer reviews and specified the topics for smart features. And we analyzed how the share of topics varied with time and analyzed diverse meta data for comparisons. The proportions of the topics for general satisfaction and satisfaction on music were increasing while the proportions of the topics for music quality, speakers and wireless speakers were decreasing over time. Though the proportions of topics for smart fea-tures were similar according to time, the share of the topics in positive reviews and importance metrics were reduced in the 2nd generation of Amazon Echo. Even though smart features were mentioned similarly in the reviews, the influential effect on satisfac-tion were reduced over time and especially in the 2nd generation of Amazon Echo.

Detection of Coffee Bean Defects using Convolutional Neural Networks (Convolutional Neural Network를 이용한 불량원두 검출 시스템)

  • Kim, Ho-Joong;Cho, Tai-Hoon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2014.10a
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    • pp.316-319
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    • 2014
  • People's interests in coffee are increasing with the expansion of coffee market. In this trend, people's taste becomes more luxurious and coffee bean's quality is considered to be very important. Currently, bean defects are mainly detected by experienced specialists. In this paper, a detection system of bean defects using machine learning is presented. This system concentrates on detecting two main defect types : bean's shape and insect damage. Convolutional Neural Networks are used for machine learning. The neural networks are comprised of two neural networks. The first neural network detects defects in the bean's shape, and the second one detects the bean's insect damage. The development of this system could be a starting point for automated coffee bean defects detection. Later, further research is needed to detect other bean defect types.

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The actual condition and improvement of audiovisual translation through analysis of subtitle in Netflix and YouTube: focusing on Korean translation. (Netflix와 Youtube 플랫폼 내의 영화 자막오역 분석을 통한 영상번역 실태와 개선점: 한국어 번역본을 중심으로.)

  • Oh, Kyunghan;Noh, Younghee
    • Journal of Digital Convergence
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    • v.19 no.3
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    • pp.25-35
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    • 2021
  • We are able to watch international multimedia anytime and anywhere, if we have the devices to connect Internet. Netflix and Youtube are the most massive and the most visited streaming platforms in the world. So If audiences are not familiar with the exotic culture such as behaviors, contexts, sarcasm, history and the current issues, It would happen a consequence that they entirely have to rely on subtitles in order to get inform. This research hereby aims to compare Korean transcriptions of the same movies streamed by the two selected platforms(Netflix and Youtube). As a result, good translation is that translators should use appropriate omissions and detailed explanations in limited time and space so that audience can concentrate on the vedio. If translators study the work in depth and spend enough time working on it, the quality of translation will definitely increase. Finally, this study contributed to the revitalization of the video translation market, which is still in the past, through the misinterpretation of videos produced at a low unit price and with minimal time without guidelines for video translation.

A Research on Image Metadata Extraction through YCrCb Color Model Analysis for Media Hyper-personalization Recommendation (미디어 초개인화 추천을 위한 YCrCb 컬러 모델 분석을 통한 영상의 메타데이터 추출에 대한 연구)

  • Park, Hyo-Gyeong;Yong, Sung-Jung;You, Yeon-Hwi;Moon, Il-Young
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.277-280
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    • 2021
  • Recently as various contents are mass produced based on high accessibility, the media contents market is more active. Users want to find content that suits their taste, and each platform is competing for personalized recommendations for content. For an efficient recommendation system, high-quality metadata is required. Existing platforms take a method in which the user directly inputs the metadata of an image. This will waste time and money processing large amounts of data. In this paper, for media hyperpersonalization recommendation, keyframes are extracted based on the YCrCb color model of the video based on movie trailers, movie genres are distinguished through supervised learning of artificial intelligence and In the future, we would like to propose a utilization plan for generating metadata.

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Personalized Data Restoration Algorithm to Improve Wearable Device Service (웨어러블 디바이스 서비스 향상을 위한 개인 맞춤형 데이터 복원 알고리즘)

  • Kikun Park;Hye-Rim Bae
    • The Journal of Bigdata
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    • v.6 no.2
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    • pp.51-60
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    • 2021
  • The market size of wearable devices is growing rapidly every year, and manufacturers around the world are introducing products that utilize their unique characteristics to keep up with the demand. Among them, smart watches are wearable devices with a very high share in sales, and they provide a variety of services to users by using information collected in real-time. The quality of service depends on the accuracy of the data collected by the smart watch, but data measurement may not be possible depending on the situation. This paper introduces a method to restore data that a smart watch could not collect. It deals with the similarity calculation method of trajectory information measured over time for data restoration and introduces a procedure for restoring missing sections according to the similarity. To prove the performance of the proposed methodology, a comparative experiment with a machine learning algorithm was conducted. Finally, the expected effects of this study and future research directions are discussed.