• Title/Summary/Keyword: AI services

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A Study on the Satisfaction and Dissatisfaction in AI Chatbot (인공지능 챗봇 서비스의 만족과 불만족에 관한 연구)

  • Yang, Chang-Gyu
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.2
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    • pp.167-177
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    • 2022
  • Unlike previous studies on AI chatbot preference that focused mostly on satisfaction, this study considered both satisfaction and dissatisfaction. This study established that (1) AI chatbot preference is driven by attractive, must-be, and one-dimensional qualities, (2) AI chatbot need to develop service strategies by taking into account users' satisfaction and dissatisfaction in accordance with preference drivers, and (3) users view interaction as a requisite and thus, if they are not satisfied with services of a AI chatbot, they don't tend to appeal their opinion and leave the service with AI chatbot. This study emphasizes that a AI chatbot that desires to be a dominant market player must provide differentiated services according to the preference drivers and must continuously encourage user participation in order to improve service quality.

Identifying Issue Changes of AI Chatbot 'Iruda' Case and Its Implications (AI 챗봇 '이루다' 논란의 이슈 변화와 시사점)

  • Choi, S.S.;Hong, A.R.
    • Electronics and Telecommunications Trends
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    • v.36 no.2
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    • pp.93-101
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    • 2021
  • The controversy over Artificial Intelligence (AI) chatbot "Iruda," which suspended its service 20 days after its launch, can be seen as the first case to inform the public of AI ethics issues. Based on this context, this study examines the controversy and social semantic formation of "Iruda" service cases using news topic modeling techniques. 963-news articles were used for the analysis, and the event's duration was analyzed based on major events, such as service start, controversy, and suspension, to understand the progress. From the analyses results, we obtain major keywords and a total of 16 topics (5, 4, 7) from the period. Finally, the implications for the development and utilization of AI services obtained through this controversy were discussed based on the analysis results.

Metadata extraction using AI and advanced metadata research for web services (AI를 활용한 메타데이터 추출 및 웹서비스용 메타데이터 고도화 연구)

  • Sung Hwan Park
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.2
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    • pp.499-503
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    • 2024
  • Broadcasting programs are provided to various media such as Internet replay, OTT, and IPTV services as well as self-broadcasting. In this case, it is very important to provide keywords for search that represent the characteristics of the content well. Broadcasters mainly use the method of manually entering key keywords in the production process and the archive process. This method is insufficient in terms of quantity to secure core metadata, and also reveals limitations in recommending and using content in other media services. This study supports securing a large number of metadata by utilizing closed caption data pre-archived through the DTV closed captioning server developed in EBS. First, core metadata was automatically extracted by applying Google's natural language AI technology. The next step is to propose a method of finding core metadata by reflecting priorities and content characteristics as core research contents. As a technology to obtain differentiated metadata weights, the importance was classified by applying the TF-IDF calculation method. Successful weight data were obtained as a result of the experiment. The string metadata obtained by this study, when combined with future string similarity measurement studies, becomes the basis for securing sophisticated content recommendation metadata from content services provided to other media.

A Study on the Method of Implementing an AI Chatbot to Respond to the POST COVID-19 Untact Era (포스트 코로나19 언택트 시대 대응을 위한 AI 챗봇 구축방법에 관한 연구)

  • Jeong, Cheonsu;Jeong, Jihwan
    • Journal of Information Technology Services
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    • v.19 no.4
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    • pp.31-47
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    • 2020
  • Recently, as the COVID-19 has spread and prolonged worldwide, the 'Untact' society is becoming routinized, and various smart technologies are leading to the spread of the 'Ontact' culture. This is because the desire of consumers to purchase a product and use the service has increased while minimizing the direct contact. In order to quickly respond to this circumstance, the percentage of the companies which are adopting Chatbot in various fields such as orders, delivery, and inquiries is increasing and they are getting a positive result. However as the demand for building Chatbot increases dramatically, there are many confusions among the companies which want to introduce Chatbot to their system, due to the lack of professional technicians and difficulties in understanding AI technologies and how to build them effectively. I believe that in the post COVID-19 era, much more companies will adopt Chatbot, and this will intensify the problem. The purpose of this study was to derive the needs for a guide on the method of buiilding a Chatbot through considering the prior research on Chatbot and analysis of the recent surge in the use of Chatbot services related to COVID-19. There are implications to presenting 5 phases of universal Chatbot implementation methodology using the platform to the stakeholders who want to introduce Chatbot to their customer so that they can understand and build Chatbot more easily and use AI Chatbot actively in response to the POST COVID-19 era.

Optimization of Action Recognition based on Slowfast Deep Learning Model using RGB Video Data (RGB 비디오 데이터를 이용한 Slowfast 모델 기반 이상 행동 인식 최적화)

  • Jeong, Jae-Hyeok;Kim, Min-Suk
    • Journal of Korea Multimedia Society
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    • v.25 no.8
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    • pp.1049-1058
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    • 2022
  • HAR(Human Action Recognition) such as anomaly and object detection has become a trend in research field(s) that focus on utilizing Artificial Intelligence (AI) methods to analyze patterns of human action in crime-ridden area(s), media services, and industrial facilities. Especially, in real-time system(s) using video streaming data, HAR has become a more important AI-based research field in application development and many different research fields using HAR have currently been developed and improved. In this paper, we propose and analyze a deep-learning-based HAR that provides more efficient scheme(s) using an intelligent AI models, such system can be applied to media services using RGB video streaming data usage without feature extraction pre-processing. For the method, we adopt Slowfast based on the Deep Neural Network(DNN) model under an open dataset(HMDB-51 or UCF101) for improvement in prediction accuracy.

UK's Digital Policies: Focusing on Strategies of AI and International Provisions (영국의 디지털 정책: AI와 국제규범 전략을 중심으로)

  • J.Y., Lee
    • Electronics and Telecommunications Trends
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    • v.37 no.6
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    • pp.11-22
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    • 2022
  • The UK is a service superpower with solid and well-developed financial and insurance services, including FinTech. Much of the UK's service industry is digital and becoming increasingly so. Primary sources constituting the UK's comparative advantage in services could be factored in business conditions driving innovation in the digital age and world-leading digital competitiveness. Therefore, this study examined the UK's digital policies. This research's focal strands were the UK's digital strategy, national artificial intelligence strategy, and digital trade objectives. As an essential insight for policymakers and other stakeholders, this study proposes that government policies in response to the digital economy are inextricably linked, leading to a critical driver for the UK's digital competitiveness.

Using Metaverse and AI recommendation services Development of Korea's leading kiosk usage service guide (메타버스와 AI 추천서비스를 활용한 국내 대표 키오스크 사용서비스 안내 개발)

  • SuHyeon Choi;MinJung Lee;JinSeo Park;Yeon Ho Seo;Jaehyun Moon
    • Proceedings of the Korea Information Processing Society Conference
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    • 2023.11a
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    • pp.886-887
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    • 2023
  • This paper is about the development of kiosks that provide four types of service. Simple UI and educational videos solve the complexity of existing kiosks and provide an intuitive and convenient screen to users. In addition, the AR function, which is a three-dimensional form, shows directions and store representative images. After storing user information in the DB, a learning model is generated using user-based KNN collaborative filtering to provide a recommendation menu. As a result, it is possible to increase user convenience through kiosks using metaverse and AI recommendation services. It is also expected to solve digital alienation of social classes who have difficulty using kiosks.

Research on Service Development Plans for the National Center for Medical Information and Knowledge: Comparison and analysis with the U.S. National Library of Medicine (국립의과학지식센터 서비스 발전 방안을 위한 연구 - 미국 국립의학도서관과의 비교·분석을 통해 -)

  • Hey-Young Rhee
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.35 no.1
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    • pp.243-272
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    • 2024
  • This study was conducted with the purpose of providing suggestions for improvement through a comparison and analysis of the services of the U.S. National Library of Medicine, the world's largest medical library, and the National Center for Medical Information and Knowledge, Korea's national medical library. Core services that need to be improved are topic-specific services, community services, services by user type, educational services, technology, facility/space services, research support services, and marketing and public relations and cooperation services. Specialized libraries are also increasingly interested in topic-specific services and public services. Efficiency in access through services for each type of user is needed, and various types of educational services that do not limit the target audience are also needed. Marketing through AI, virtual reality, and technology, facility, and space services to support the disabled, research support services centered on research ethics, research grants, and programs, and collaborative services with domestic and international libraries, academic societies, institutions, and local communities in other related fields and publicity are also needed.

Intelligent Records and Archives Management That Applies Artificial Intelligence (인공지능을 활용한 지능형 기록관리 방안)

  • Kim, Intaek;An, Dae-Jin;Rieh, Hae-young
    • Journal of Korean Society of Archives and Records Management
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    • v.17 no.4
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    • pp.225-250
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    • 2017
  • The Fourth Industrial Revolution has become a focus of attention. Artificial intelligence (AI) is the key technology that will lead us to the industrial revolution. AI is also used to facilitate efficient workflow in records and archives management area, particularly abroad. In this study, we introduced the concept of AI and examined the background on how it rose. Then we reviewed the various applications of AI with prominent examples. We have also examined how AI is used in various areas such as text analysis, and image and speech recognition. In each of these areas, we have reviewed the application of AI from the viewpoint of records and archives management and suggested further utilization of the methods, including module and interface for intelligent records and archives information services.

A Case Study on an Artificial Intelligence Fashion Curation Practice Subject through Industrial-academic Project-based Learning (산학 연계 프로젝트 기반 학습(PBL)을 활용한 AI 패션 큐레이션 실습 교과목 운영 사례 연구)

  • An, Hyosun;Park, Minjung
    • Fashion & Textile Research Journal
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    • v.23 no.3
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    • pp.337-346
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    • 2021
  • In the fourth industrial revolution, fashion students are expected to work with various technologies to show creativity. This study aimed to conduct project-based learning(PBL) in collaboration with industry experts to design and operate artificial intelligence(AI) in the practice subject of fashion curation through the industrial academic teaching method. We first looked at teaching methods and strategies incorporating PBL in various academic fields. Next, we analyzed fashion projects and fashion curation services applying AI. Then through the question-and-answer method and by consulting with industry experts, we developed a curriculum for AI fashion curation, applying PBL(fashion market and trend analysis; new styles and time, place, and occasion planning; AI machine learning data set production; curation model development; and evaluation) suitable for the university's educational environment, information technology company conditions, and fashion students. As part of a close cooperation system with the industry, we conducted a 15-week Fashion Project II (Capstone Design) course and evaluated the outcomes and student satisfaction with the course. Students were able to develop new style, and time, place, and occasion categories and to utilize strategies for AI fashion curation services reflecting the unique needs of Millennials and Generation Z. Students showed high satisfaction with the curriculum. Further, it was confirmed that the study successfully applied PBL in class using AI technology in fashion education.