$\require{mediawiki-texvc}$

연합인증

연합인증 가입 기관의 연구자들은 소속기관의 인증정보(ID와 암호)를 이용해 다른 대학, 연구기관, 서비스 공급자의 다양한 온라인 자원과 연구 데이터를 이용할 수 있습니다.

이는 여행자가 자국에서 발행 받은 여권으로 세계 각국을 자유롭게 여행할 수 있는 것과 같습니다.

연합인증으로 이용이 가능한 서비스는 NTIS, DataON, Edison, Kafe, Webinar 등이 있습니다.

한번의 인증절차만으로 연합인증 가입 서비스에 추가 로그인 없이 이용이 가능합니다.

다만, 연합인증을 위해서는 최초 1회만 인증 절차가 필요합니다. (회원이 아닐 경우 회원 가입이 필요합니다.)

연합인증 절차는 다음과 같습니다.

최초이용시에는
ScienceON에 로그인 → 연합인증 서비스 접속 → 로그인 (본인 확인 또는 회원가입) → 서비스 이용

그 이후에는
ScienceON 로그인 → 연합인증 서비스 접속 → 서비스 이용

연합인증을 활용하시면 KISTI가 제공하는 다양한 서비스를 편리하게 이용하실 수 있습니다.

Suggestion of a Big Data-Driven Design Evaluation Matrix: Hyundai Motors and Mercedes Benz
빅 데이터 기반 디자인 평가 매트릭스 제안 : 현대자동차와 메르세데스 벤츠를 중심으로 원문보기

Archives of design research, v.34 no.3 = no.139, 2021년, pp.211 - 227  

Lee, Yonghyuck ,  Lee, Yonghyuck ,  Youn, Daemyung ,  Youn, Daemyung ,  Hwang, Senhyun ,  Hwang, Senhyun ,  Rhi, Joomyung ,  Rhi, Joomyung

초록이 없습니다.

참고문헌 (41)

  1. Asiedu, Elizabeth. Foreign Direct Investment in Africa: The Role of Natural Resources, Market Size, Government Policy, Institutions and Political Instability. The World economy, vol.29, no.1, 63-77.

  2. 안효선, 박민정. 빅데이터 텍스트 분석을 기반으로 한 패션디자인 평가 연구 -디자인 속성과 감성 어휘의 의미연결망 분석을 중심으로-. 한국의류학회지 = Journal of the Korean Society of Clothing and Textiles, vol.42, no.3, 428-437.

  3. Chin, H., & Yi, M. Y. (2017). A Study on the Influence of Contents of Internet News Comments on the Acceptance of New Car Products. Korea Information Science Society, 605-608 

  4. 10.1145/511446.511464 

  5. Farquhar, P. H. (1990). Managing brand equity. Journal of advertising research, 30(4), RC-7 

  6. Godes, David, Mayzlin, Dina. Using Online Conversations to Study Word-of-Mouth Communication. Marketing science : the marketing journal of TIMS/ORSA, vol.23, no.4, 545-560.

  7. 황해정, 심혜린, 최준호. 빅데이터 분석을 활용한 사용자 경험 평가 방법론 탐색 : 아마존 에코에 대한 온라인 리뷰 분석을 중심으로. 한국콘텐츠학회논문지 = The Journal of the Korea Contents Association, vol.16, no.8, 517-528.

  8. 조정태, 최상현. 영화리뷰 감성 분석을 통한 평점 예측 연구. 경영과 정보연구 = Management & information systems review, vol.34, no.3, 161-177.

  9. Kang, S. J., & Kim, M. J. (2018). The Propose a Legislation Bill to Apply Autonomous Carsand the Study for Status of Legal and Political Issues. Journal of Korea Technology Innovation Society 21(1), 151-200 

  10. Kim, S. H. (2016, Apr). Reading the World: The 4th Industrial Revolution of Automobiles and Jeju Green Big Bank. Maeil Busines, Retrived form https://www.mk.co.kr/opinion/contributors/view/2016/04/253746/ 

  11. Kim, S. T. (2017). A Methodology for privacy incident inspecting System based on Web Crawler (Unpublished Master's thesis). Soongsil University, Seoul, Korea 

  12. Kim, D. W. (2013). Big Data Use Cases of the Sector. Dong-A University Business Research Center, 34, 39-52 

  13. Kim, J. C. (2017, March). Fundamental questions about big data utilization. CIO, Retrieved from https://www.ciokorea.com/insider/33206 

  14. Kim, D. W. (2013). Big Data Use Cases of the Sector. Dong-A University Business Research Center, 34, 39-52 

  15. Kim, E. H. (2012). Study on female Consumer Perceived Quality of Automobile Design through Usability Evaluation (Master's thesis). Sungshin Women's University, Seoul 

  16. Korea Institute of Design Promotion. (2016). User Experience Quality Guidebook 

  17. Kim, Kyung Hwan, Park, Kyung Jin. A study on the car exterior tuning design sensibilities elements analysis - focused on customizing tuning parts -. 한국과학예술포럼 = Korea science & art forum, vol.20, 59-.

  18. Lee, G. S., & Woo, J. P. (2018). Analysis of Interest in Automobiles Using Naver BigData. Korea Ditribution Association, 98-102 

  19. Ministry of Trade, Industry and Energy. (2018). 2019 Korea Design Statistical Data, 121-163 

  20. Park, C. S., & Shin, S. J. (2009). Relationship analysis between Customer Satisfaction Index and Market Share in Automotive and IT industries. In Proceedings of the Korea Information Processing Society Conference (pp. 939-940). Korea Information Processing Society 

  21. Petty, Richard E., Cacioppo, John T.. The effects of involvement on responses to argument quantity and quality: Central and peripheral routes to persuasion.. Journal of personality and social psychology, vol.46, no.1, 69-81.

  22. Park, B. Y., Kim, S. S., Kang, J. H., & Jun, M. S. (2018). Trend of Big data Analysis Platform Service. In Proceedings of the Korea Information Processing Society Conference (pp. 589-591). Korea Information Processing Society 

  23. Park, G, J. (2014). AWS [Building a Big Data Analysis Class Environment with Amazon Cloud AWS]. Industrial Engineering Magazine, 21(3), 62-66 

  24. Park, J. Y., Lee, J., Seo, B. G., Kim, K. W., Yoo, I. J., Lee, H., Lee, S., Lee, Y., Park, Y., Park, K., & Park. D. (2019). A Study on the Methodology of Data-Driven UX Concept Development. Proceedings of HCI KOREA 2019, 633-637 

  25. Qiyu, J. (2020). The Effect of Wool Coat Image by Country of Origin on Chinese Consumer's Perceived Quality, Product Attitude and Purchase Intention : Focused on Moderating effect of the Brand Familiarity (Master's thesis). Ewha Women's University, Seoul. (UCI No.I804:11048-000000163368) 

  26. Shin, H. (2021, Feb 04). From a smartphone to an Apple car...Camera parts stock is up. Sedaily, Retrived form https://www.sedaily.com/NewsVIew/22IEF2K3XX 

  27. South Korea Ministry of Trade, Industry and Energy. (2020). Annual trends in the automotive industry in 2019 

  28. Sun, A., Lachanski, M., Fabozzi, F.J.. Trade the tweet: Social media text mining and sparse matrix factorization for stock market prediction. International review of financial analysis, vol.48, 272-281.

  29. Song, N, Y. (2018). Estimation of Explicit Functions using Deep Learning (Unpublished Master's thesis). Myongji University, Seoul 

  30. Viveros-Jiménez, Francisco, Sánchez-Pereza, Miguel A., Gómez-Adorno, Helena, Posadas-Durán, Juan Pablo, Sidorov, Grigori, Gelbukh, Alexander. Improving the Boilerpipe Algorithm for Boilerplate Removal in News Articles Using HTML Tree Structure. Computación y sistemas, vol.22, no.2,

  31. Yatskov, A. K., Varlamov, M. I., Turdakov, D. Yu.. Extraction of Data from Mass Media Web Sites. Programming and computer software, vol.44, no.5, 344-352.

  32. Yoon, H. K. (2013). Research on the Application Methods of Big Data within the Cultural Industry. Academic association of global cultural contents, 10, 157-179 

  33. Yoon, H. S. (2017). A Preliminary Study on Regulation of Emerging Technologies. Journal of Law & Economic Regulation,1, 7-29 

  34. Yoon, D. M., Lee, Y., H., & Lee, B. G. (2020). Proposal of Brand Evaluation Map through Big Data : Focus on The Hyundai Motor's Product Evaluation. Journal of Information Technology Services, 19, 1-11 

  35. Yun, P. S. (2019). Implementation of AWS-based deep learning platform using streaming server and performance comparison experiment. Electronic & Information Research Information Center, 12(6), 591-596 

  36. Zeithaml, Valarie A.. Consumer Perceptions of Price, Quality, and Value: A Means-End Model and Synthesis of Evidence. Journal of marketing, vol.52, no.3, 2-22.

  37. 장해, 박주식. 온라인 구전 신뢰성의 선행요인과 2차 구전의도에 미치는 영향 -온라인 구전 관여도의 조절효과를 중심으로-. 경영과 정보연구 = Management & information systems review, vol.34, no.1, 81-101.

  38. Cloud computing with AWS. (n.d.). Retrieved December 12, 2020, from https://aws.amazon.com/what-is-aws/?nc1=h_ls 

  39. Amazon Lex Documentation. (n.d.). Retrieved Apr 5, 2021, from https://docs.aws.amazon.com/lex/ 

  40. Chris, P. (2019, Aug). Google Cloud vs AWS vs Azure. eWEEK, Retrieved from https://www.eweek.com/cloud/at-a-high-level-aws-vs-azure-vs-google-cloud 

  41. Web Crawler. (n.d.). Retrieved Sep 30, 2020, from https://en.wikipedia.org/wiki/WebCrawler#cite_ref-:1_2-2 

섹션별 컨텐츠 바로가기

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

AI-Helper 아이콘
AI-Helper
안녕하세요, AI-Helper입니다. 좌측 "선택된 텍스트"에서 텍스트를 선택하여 요약, 번역, 용어설명을 실행하세요.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.

선택된 텍스트

맨위로