한국융합학회논문지 (Journal of the Korea Convergence Society)

  • 제11권6호
  • /
  • Pages.163-171
  • /
  • 2020
  • /
  • 2233-4890(pISSN)
  • /
  • 2713-6353(eISSN)
한국융합학회 (Korea Convergence Society)
권호 표지
DOI QR코드

DOI QR Code

영화 콘텐츠 큐레이션과 메타데이터 표준 연구의 동향 분석 -예술경영 관점으로-

Trend Analysis of Movie Content Curation and Metadata Standards Research - Focus on the Art Management Perspective -

  • 배승주 (경성대학교 디지털미디어학부)
  • 투고 : 2020.04.06
  • 심사 : 2020.06.20
  • 발행 : 2020.06.28
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

본 연구는 국내 영화 콘텐츠 큐레이션 연구에 나타난 메타데이터 연구들을 찾아서 연도별로 내용과 변화를 예술 경영의 관점에서 분석하는 것이다. 큐레이션과 추천시스템은 모두 그 바탕에 메타데이터의 기능이 작동하고 있다. 연구의 목적은 디지털 콘텐츠에서 큐레이션과 추천시스템이 어떻게 다른가를 확인하는 것이다. 연구절차와 방법은 '영화'와 '메타데이터'를 키워드로 논문을 검색하고, 이를 연도별 연구경향, 연구내용의 목적, 용도별 분석, 추천 방식의 유형에 따른 변화의 4단계로 분석하는 과정을 거쳤다. 연구 결과는 영화 메타데이터 연구는 이용자 측면의 연구에 관심이 높고, 도입단계, 추천방식 진화단계, 공유와 참여 단계로 발전하고 있으며, 영화 큐레이션은 검색지원, 콘텐츠 기반, 협력필터링, 하이브리드, 인공지능, 큐레이션의 6단계로 진화하였다는 결론을 얻은 것이다. 이 연구는 장르별 예술경영을 위한 메타데이터 개발에 기여할 것으로 기대한다.

This study analyzed the contents and changes by year of metadata research that appeared in the study of domestic movie curation from the viewpoint of art management. The research method used thesis search site to search 'movie' and 'metadata' as keywords, and analyzed them in 4 stages of change according to the research trend by year, purpose of research content, analysis by use, and type of recommendation method. As for research results, movie metadata research is highly interested in user-side research, and is developing from an introduction stage to an evolutionary stage of recommendation to a sharing and participation stage. It was concluded that movie curation evolved into 6 stages: search support, content-based, collaborative filtering, hybrid, artificial intelligence, and curation.

키워드

참고문헌

  1. J. E. Tae, K. H. Jung & H. J. Song. (2016). A study of Convergence Relationship between Post-Modern aspects and storytelling from Imaging Content Production. Journal of the Korea Convergence Society, 7(6), 177-184. https://doi.org/10.15207/JKCS.2016.7.6.177
  2. G. J. Moon. (2018). The Scenery of the Urban Residence Represented in Korean Films of the Liberation Period. Journal of the Korea Convergence Society, 9(4), 119-125. https://doi.org/10.15207/JKCS.2018.9.4.119
  3. S. H. Lee. (2019). A Longitudinal Study on the Supply & Demand-side Diversity of Digital Media : TV Channel & VOD Data of 2012-2017. Journal of the Korea Convergence Society, 10(8), 137-144. https://doi.org/10.15207/JKCS.2019.10.8.137
  4. J. E. Son, S. B. Kim, H. J. Kim & S. Z. Cho. (2015). Review and Analysis of Recommender System. Journal of The Korean Institute Of Industrial Engineers, 41(2), 185-208. https://doi.org/10.7232/JKIIE.2015.41.2.185
  5. N. Beagrie. (2008). Digital curation for science, digital libraries, and individuals. International Journal of Digital Curation, 1(1), 3-16. https://doi.org/10.2218/ijdc.v1i1.2
  6. L. Madden. (2007). Digital curation at the Library of Congress: Lessons learned from American Memory and the archive ingest and handling test. DigCCurr2007, April 18-20, 2007, Chapel Hill, NC.
  7. E. Yakel. (2007). Digital curation. OCLC Systems & Services: International digital library perspectives.
  8. D. Kasch. (2013). Social media selves: College students' curation of self and others through Facebook (Doctoral dissertation, UCLA).
  9. S. S. Lee & I. S. Song. (2005). A Study on Metadata of Technology Trends Information Based on NewsML. JOURNAL OF THE KOREAN SOCIETY FOR LIBRARY AND INFORMATION SCIENCE, 39(3), 183-205. https://doi.org/10.4275/KSLIS.2005.39.3.183
  10. S. R. Yoo. (2010). A Diagnostic Analysis of Metadata R&D Status in Korea. JOURNAL OF THE KOREAN SOCIETY FOR LIBRARY AND INFORMATION SCIENCE, 44(2), 405-426. https://doi.org/10.4275/KSLIS.2010.44.2.405
  11. B. J. Jeon. (2011). A Study on the Applying Metadata Standards in Cadastral Information for increasing its Utilization. Journal of the Korean Cadastre Information Association, 13(1), 81-92.
  12. M. H. Lee, W. G. Lee, H. M. Yoon, S. H. Shin & J. C. Ryou. (2011). Comparison and Analysis of Science and Technology. Journal Metadata. JOURNAL OF THE KOREA CONTENTS ASSOCIATION, 11(9), 515-523. https://doi.org/10.5392/JKCA.2011.11.9.515
  13. T. W. Nam & S. M. Lee. (2010). Study on the Semantic Extension of the Concept of Metadata. JOURNAL OF THE KOREAN SOCIETY FOR LIBRARY AND INFORMATION SCIENCE 44(4), 373-393. https://doi.org/10.4275/KSLIS.2010.44.4.373
  14. Priscilla Caplan. (2003). Metadata Fundamentals for All Librarians. Chicago : AMERICAN LIBRARY ASSOCIATION.
  15. Y. Kim & S. B. Moon. (2006). A Study on Hybrid Recommendation System Based on Usage Frequency for Multimedia Contents. Journal of the Korean Society for Information Management, 23(3), 91-125. https://doi.org/10.3743/KOSIM.2006.23.3.091
  16. S. H. Ann & C. K. Shi. (2008). Movie Recommendation System Based on Cultural Metadata. Korea Information Science Society Journal, 35(1A), 78-79.
  17. J. H. Park & Y. H. Cho. (2011). Social Network Analysis for the Effective Adoption of Recommender Systems. Journal of Intelligence and Information systems, 17(4), 305-316. https://doi.org/10.13088/JIIS.2011.17.4.305
  18. H. G. Choi & E. J. Hwang. (2012). Emotion-based Music Recommendation System based on Twitter Document Analysis. Journal of KIISE : Computing Practies and Letters, 18(11), 732-767.
  19. M. D. Hong, K. J. Oh, M. H. Ga & G. S. Jo. (2013). Content based Recommendation Based on Social Network for Personalized News Services. Journal of Intelligence and Information systems, 19(3), 57-71. https://doi.org/10.13088/jiis.2013.19.3.057
  20. J. Y. Kim & S. W. Lee. (2013). The Ontology Based, The Movie Contents Recommendation Scheme, Using Relations of Movie Metadata. Journal of Intelligence and Information systems, 19(3), 25-44. https://doi.org/10.13088/jiis.2013.19.3.025
  21. M. J. Kim & Y. H. Cho. (2015). A Multimodal Profile Ensemble Approach to Development of Recommender System Using Big Data. Journal of Intelligence and Information systems, 21(4), 93-110. https://doi.org/10.13088/jiis.2015.21.4.093
  22. S. I. Choi, Y. J. Hyun & N. G. Kim. (2015). Improving Performance of Recommendation Systems Using Topic Modeling. Journal of Intelligence and Information systems, 21(3), 101-116. https://doi.org/10.13088/jiis.2015.21.3.101
  23. H. L. Jin, H. S. Kim, K. J. Chung & Y. A. Kang. (2019). A Proposal to improve movie curation service through categorizing WATCHA users. Journal of The HCI Society of Korea, 2, 587-591.
  24. W. S. Koo, B. W. Oh & K. J. Han. (1995). A Study on a VOD System based on UNIX Server and PC Clients. Proceedings of The Korean Institute of Information Scientists and Engineers, 22(2A), 213-216.
  25. S. W. Yang, B. N. R. Bae & Y. M. Ro. (2003). Study of Mobile Environment - Based Video Selection and Summary Service System. Proceedings of The Korean Institute of Information Scientists and Engineers, 30(2 II), 460-462.
  26. M. H. Kim, J. H. Nam & J. W. Hong. (2006). Lossless Video Watermarking for effective digital content management with UCI. Proceedings of The Korean Institute of Information Scientists and Engineers, 33(2C), 544-547.
  27. S. A. Mok, C. H. Kim & J. K. Paik. (2008). Media Production Environment Using Metadata based on Advanced Authoring Format. JOURNAL OF BROADCAST ENGINEERING 13(2), 274-282. https://doi.org/10.5909/JBE.2008.13.2.274
  28. S. K. Ko, S. M. Choi & Y. S. Han. (2010). Movie Recommendation Technique based on Periodical Genre Correlations. Proceedings of Korea Multimedia Society, 109-111.
  29. Y. H. Lim, C. H. Kim & J. K. Paik. (2011). Efficient Film Post Production Process using Metadata on the eXtensible Markup Language. JOURNAL OF BROADCAST ENGINEERING 16(3), 439-447. https://doi.org/10.5909/JEB.2011.16.3.439
  30. J. S. Lee, S. J. Jang & S. P. Lee. (2011). Design and Implementation of content information enrichment service in the IPTV environment. Proceedings of The Korean Society Of Broad Engineers, 424-427.
  31. B. H. Kim & B. T. Zhang. (2014). Movie Recommendation Using Co-Clustering by Infinite Relational Models. Journal of Korean Institute of Intelligent Systems, 24(4), 443-449. https://doi.org/10.5391/JKIIS.2014.24.4.443
  32. Y. Jin, J. S. Kim & J. W. Kim. (2014). Product Community Analysis Using Opinion Mining and Network Analysis - Movie Performance Prediction Case -. Journal of Intelligence and Information Systems, 20(1), 49-65. https://doi.org/10.13088/jiis.2014.20.1.049
  33. H. B. Bang, H. W. Lee & J. H. Lee. (2015). A Content-based TV Program Recommendation System Using Age and Plots. Proceedings of the Korean Society of Computer Information Conference, 23(1), 51-54.
  34. S. U. Kang, S. H. Park & G. G. Lim. (2016). The Improved UCI Identifier Syntax for Convergence Digital Contents. Journal of the Institute of Electronics and Information Engineers, 53(9), 82-88. https://doi.org/10.5573/IEIE.2016.53.9.082
  35. J. W. Ok, H. J. Kim, D. H. Cho, H. S. Ju, H. C. Lee, Theresia Saputri & S. W. Lee. (2017). Predicting The Number of Audience and Breakeven Point Attainment based on Movie Metadata. Proceedings of The Korean Institute of Information Scientists and Engineers, 1932-1934.
  36. D. H. Cho, H. J. Kim, J. W. Ok, H. S. Ju, S. W. Lee. & Y. J. Choi. (2018). Web Service Implementation for Predicting the Number of Audience and BEP of Movie Based on Metadata. Proceedings of Symposium of the Korean Institute of communications and Information Sciences, 920-921.