References
- 국가기록원 (2017). 2017 국가기록원 주요업무 참고자료집. 대전: 국가기록원.(National Archives of Korea (2017). 2017 National Archives of Korea key business references. Daejeon: National Archives of Korea.)
- 박전규 (2017). 딥러닝 기법 적용 다국어 음성인식기술. 2017 기록관리 R&D 공동학술 세미나. 국가기록원. https://www.youtube.com/watch?v=XZKvnSQCq6I(Park, Jeon-kyu (2017). Multilingual speech recognition technology using deep learning technique. 2017 Record Management R&D Joint Academic Seminar. National Archives of Korea. Retrieved from https://www.youtube.com/watch?v=XZKvnSQCq6I)
- 박춘원 (2017). 4차 산업혁명 시대 기업 동영상 기록 관리와 동적 메타데이터. 2017 한국기록관리학회 춘계학술대회 및 한국기록과 정보.문화학회, 대한기록정보경영포럼 공동 주최 학술회의. 2017. 4. 29일. 서울: 한국외국어대학교.(Park, Choon-won (2017). Enterprise video record management and dynamic metadata in the 4th industrial revolution era. 2017 Spring Conference of Korean Society of Archives and Records Management and Joint Conference of Korean Society of Archival, Information and Cultural Studies, Korea Records and Information Management Forum. 29 April, 2017. Seoul: Hankuk University of Foreign Studies.)
- 세미콘 네트웍스 (2017). 사업분야. 검색일자: 2017. 10. 18. http://www.sns.co.kr/scripts/rid_division.asp?lKey=02&mKey=02(Semicon Networks (2017). Business areas. Retrieved October 18, 2017, from http://www.sns.co.kr/scripts/rid_division.asp?lKey=02&mKey=02)
- 송철의 (2016). [한국어와 인공지능] 송철의 국립국어원장 "한국어 AI 시대의 기초는 말뭉치... 제2의 세종계획 추진해야." 조선비즈. http://biz.chosun.com/site/data/html_dir/2016/10/09/2016100900328.html(Song, Cheol-eui (2016). [Korean language and Artificial Intelligence] Song Cheol-Eui, Chair of National Institute of Korean Language: The foundation AI in Korean language is the corpus... the second Sejong project should be promoted. ChosunBiz. Retrieved from http://biz.chosun.com/site/data/html_dir/2016/10/09/2016100900328.html)
- 스토리안트 (2017). 지능형 기록관리 업무지원 시스템. 검색일자: 2017. 10. 13. http://www.storyant.com/?page_id=6092(Storyant (2017). Intelligent records management business system. Retrieved October, 13, 2017, from http://www.storyant.com/?page_id=6092)
- 신은희, 이대철, 배정미, 김현민, 신지윤, 이상준 (2017). 지능형 콘텐츠 기술 발전 전략 연구. 연구보고서. 2017년 2월 28일. 한국콘텐츠진흥원.(Shin, Eun-hee, Lee, Dae-cheol, Bae, Jeong-mi, Kim Hyun-min, Shin Ji-yoon, & Lee Sang-jun (2017). A study on development strategy of intelligent contents technology. February 28, 2017. Research report. Seoul: Korea Creative Content Agency.)
- 안대진 (2017). 지능형 기록정보서비스 방안. 제9회 전국기록인대회 발표자료집, 52-57.(An, Dae-jin (2017). Intelligent records and archival Information service. The 9th National Archivist Conference. Presentation materials, 52-57.)
- 오대석 (2017. 10. 19). 스스로 바둑 깨우친 '알파고 제로'... AI '새 이정표'. 전자신문. http://www.etnews.com/20171019000101(Oh, Dae-suk (2017. 10. 19). 'Alpha Go Zero' which learned Go by itself... AI's 'new milestone' for AI. Electronic Times Internet. Retrieved from http://www.etnews.com/20171019000101)
- 이웅 (2017. 10. 9). 인공지능용 한국어 말뭉치 155억어절 구축... 5년간 175억 지원. 연합뉴스. http://www.yonhapnews.co.kr/bulletin/2017/10/08/0200000000AKR20171008048600005.HTML(Lee, Woong (2017. 10. 9). Korean corpus for artificial intelligence will be built up to 15.5 billion words... 17.5 billion won will be supported for 5 years. Yonhap News. Retrieved from http://www.yonhapnews.co.kr/bulletin/2017/10/08/0200000000AKR20171008048600005.HTML)
- 지형철 (2017. 2. 21). 말하고 듣는 AI시대... 뒤처진 한국어. KBS 뉴스. http://news.kbs.co.kr/news/view.do?ncd=3432955(Ji, Hyung-chul (2017). Era of talking and listening via AI… Korean is not ready. KBS News. Retrieved October 20, 2017, from http://news.kbs.co.kr/news/view.do?ncd=3432955)
- 추형석, 안성원, 김석원 (2016). AlphaGo의 인공지능 알고리즘 분석. SPRi Issue Report 2016 3. 성남: 소프트웨어정책연구소.(Chu, Hyung-suk, An, Sung-won, & Kim, Suk-won (2016). AlphaGo's AI algorithm analysis. SPRi Issue Report. March 2016. Seongnam: Software Policy & Research Institute.)
- Ai (2017). Text APIs. Retrieved October 14, 2017, from https://ai-applied.nl/text-apis/
- AIBRIL (2017). Service. ABRIL의 서비스를 소개합니다. Retrieved October 20, 2017, from https://www.aibril.com/web/api/getApiIndex.do
- Amazon (2017). Amazon rekognition. Retrieved October 15, 2017, from https://aws.amazon.com/ko/rekognition/
- Amazon AI (2017). AWS 기반 인공 지능. Retrieved October 14, 2017, from https://aws.amazon.com/ko/amazon-ai/
- Bahde, A. (2017). Conceptual data visualization in archival finding aids: preliminary user responses. portal: Libraries and the Academy, 17(3), 485-506. https://doi.org/10.1353/pla.2017.0031
- BBC (2014). Turing machine. Retrieved October 14, 2017, from http://www.bbc.com/news/technology-27762088
- Daines III, J. G. & Nimer, C. L. (2011). Re-imagining archival display: Creating user-friendly finding aids. Journal of Archival Organization, 9(1), 4-31. https://doi.org/10.1080/15332748.2011.574019
- Dartmouth (2006). Dartmouth artificial intelligence conference: The next 50 years. Retrieved October 20, 2017, from https://www.dartmouth.edu/-ai50/homepage.html
- DBPedia Contribute (2017). Retrieved October 17, 2017, from http://wiki.dbpedia.org/contribute
- Deep Blue (2011). Deep blue. Retrieved October 14, 2017, from http://www-03.ibm.com/ibm/history/ibm100/us/en/icons/deepblue/
- ETRI (2017). 기술이전 홈페이지. Retrieved October 18, 2017, from https://itec.etri.re.kr/itec/sub02/sub02_01.do
- Google Cloud AI (2017). Retrieved October 20, 2017, from https://cloud.google.com/products/machine-learning/
- Google OCR (2017). Retrieved October 18, 2017, from https://cloud.google.com/vision/docs/ocr
- IBM BlueMix (2017). Retrieved October 18, 2017, from https://www.ibm.com/cloud-computing/bluemix/ko
- John Danaher (2016. 7. 13). Reverse turing tests: Are humans becoming more machine-like? Philosophical Disquisitions. Retrieved from http://philosophicaldisquisitions.blogspot.kr/2016/07/reverse-turing-tests-are-humans.html
- Krause, M. G. & Yakel, E. (2007). Interaction in virtual archives: the polar bear expedition digital collections next generation finding aid. American Archivist, 70(2), 282-314. https://doi.org/10.17723/aarc.70.2.lpq61247881t10kv
- Kumar, V. (2014). Making 'Freemium' work: many start-ups fail to recognize the challenges of this popular business model. Harvard Business Review 92, no. 5 (May 2014), 27-29.
- Kurzweil, R. (2005). The singularity is near: When humans transcend biology. New York: The Viking Press.
- LeCun, Y. et al. (1998). Gradient-based learning applied to document recognition, Proc. of The IEEE 86(11), 2278-2324. https://doi.org/10.1109/5.726791
- Markoff, John (2011. 2. 17). Computer wins on 'Jeopardy!': Trivial, It's not. New York Times, 16. Retrieved from http://www.nytimes.com/2011/02/17/science/17jeopardy-watson.html
- Mikolov, T. et al. (2013). Efficient estimation of word representation in vector space. arXiv preprint arXiv:1301.3781.
- Moorhead, Patrick (2015. 3. 27). NVIDIA GTC: The race to perfect voice recognition using gpus. Forbes. Mar 27, 2015. Retrieved from https://www.forbes.com/sites/patrickmoorhead/2015/03/27/nvidia-gtc-the-race-to-perfect-voice-recognition-using-gpus/#7be1add847ee
- Myers, Erin (2017. 10. 11). Little known facts about speech recognition technology. October 11, 2017. Retrieved October 14, 2017, from https://www.temi.com/blog/2017/10/11/little-known-facts-about-speech-recognition-technology/
- National Archives and Records Administration (2014). Managing government records directive. Automated electronic records management report/plan. Washington, DC: Office of the Chief Records Officer for the U.S. Government.
- National Archives of Australia (2017). Whole-of-government digital records platform. Retrieved October 8, 2017, from http://www.naa.gov.au/information-management/digital-transition-and-digital-continuity/information-is-managed-digitally/Whole-of-Government-Digital-Records-Platform.aspx
- Neotalogic (2016). Artificial intelligence in law: The state of play 2016. Retrieved October 19, 2017, from https://www.neotalogic.com/2016/02/28/artificial-intelligence-in-law-the-state-of-play-2016-part-1/
- Omeka (2017). Text Analysis. Retrieved October 12, 2017, from https://omeka.org/classic/docs/Plugins/Text_Analysis2/
- Oracle (2017). Multi-dimensional evolution of computing. Cloud-native-devops-workshop. Retrieved October 23, 2017, from https://github.com/oracle/cloud-native-devops-workshop/blob/master/containers/docker001/images/006-evolution.jpg
- Price, Rob (2017. 8. 21). Microsoft's AI is getting crazily good at speech recognition. Business Insider. Aug. 21, 2017. Retrieved from http://uk.businessinsider.com/microsofts-speech-recognition-5-1-error-rate-human-level-accuracy-2017-8
- Samuel, Arthur (1959). Some studies in machine learning using the game of checkers. IBM Journal, 3(3), 210-229. https://doi.org/10.1147/rd.33.0210
- Satell, Greg (2016). 3 Reasons to believe the singuarlity is near. Retrieved from https://www.forbes.com/sites/gregsatell/2016/06/03/3-reasons-to-believe-the-singularity-is-near
- Solon, Olivia (2017. 1. 30). Oh the humanity! Poker computer trounces humans in big step for AI. Retrieved from https://www.theguardian.com/technology/2017/jan/30/libratus-poker-artificial-intelligence-professional-human-players-competition
- Sun, C., Shrivastava, A., Singh, S., & Gupta, A. (2017). Revisiting unreasonable effectiveness of data in deep learning era. Retrieved from https://arxiv.org/pdf/1707.02968.pdf
- The National Archives (2017). Digital strategy. Retrieved October 13, 2017, from http://www.nationalarchives.gov.uk/documents/the-national-archives-digital-strategy-2017-19.pdf
- Turing, A. M. (1950). Computing machinery and intelligence. Mind(49), 433-460.
- White House (2016). Preparing for the Future of Artificial Intelligence. Executive Office of the President National Science and Technology Council. Committee on Technology. Retrieved from https://obamawhitehouse.archives.gov/sites/default/files/whitehouse_files/microsites/ostp/NSTC/preparing_for_the_future_of_ai.pdf
- World Economic Forum (2016). World Economic Forum Annual Meeting 2016: Mastering the Fourth Industrial Revolution. Retrieved from http://www3.weforum.org/docs/WEF_AM16_Report.pdf
- Zhang, X. & LeCun, Y. (2015). Text understanding from scratch. arXiv preprint. Retrieved from arXiv:1502.01710v5