관광 지식베이스와 스마트 관광 서비스 (Knowledge base and Smart Tourism)

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  2019년 2월 22일 한국관광공사 서울센터에서 있었던 "스마트관광&빅데이터,AI세미나 : 관광산업과 인공지능의 역할" 세미나에서 발표했던 스마트 관광과 지식베이스 발표자료 입니다.
  • 1. Photo by rawpixel on Unsplash 관광 지식베이스와 스마트 관광 서비스 이명진 Ph.D. 주식회사 리스트 CTO
  • 2. Pebble Beach and 17-Mile Drive have a storied tradition as a bucket-list destination. But as they aim to attract a new generation of younger and more tech savvy travelers, this has increased expectations for how to create a more engaging and personalized journey. https://www.pebblebeach.com/content/uploads/Pebble_Beach_Arrowhead_13557_copy-ES.jpg
  • 3. to the application of information and communication technology for developing innovative tools in tourism Smart Tourism Internet of Tings Mobile Communication Cloud Computing Artificial Intelligence • the network of devices such as vehicles, and home appliances • realize increased operational efficiency and more personalized guest experience • on sharing of resources to achieve coherence and economies of scale • cost-effective innovation quickly • the primary interaction channel • In 2019 the number of mobile phone users is forecast to reach 4.68 billion. • intelligence demonstrated by machines • automated, personalized and intelligent travel services http://www.wi2wi.com/images/bodyscreen1.png https://iwsinc.com/wp-content/uploads/2018/05/pillphone-smartphone.png http://3.bp.blogspot.com/-ICnZfeA1hJ8/VX5k0xF3vXI/AAAAAAAAN38/QgbPAoQJHbY/s1600/Cloud-computing-concept_nobg.png https://www.kreyonsystems.com/images/AIbusinessfinal.png
  • 4. Artificial Intelligence • the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals • a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation https://clipground.com/images/5-pieces-clipart-10.jpg Symbolic Approach Sub-Symbolic Approach describing and manipulating our knowledge of the world as explicit symbols calculations according to some principles that have demonstrated to be able to solve problems AI Approaches
  • 5. https://sift.com/image/sift-edu/prevent-fraud/fraud-solutions/machine-learning-2x.png https://cdn-images-1.medium.com/max/1200/1*U0-H9Af2FT-DK0nnHhaoJQ.png Sub-Symbolic AI • to approach intelligence without specific representations of knowledge • the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention
  • 6. https://www.researchgate.net/publication/221152559_A_Path-based_Relational_RDF_Database https://twitter.com/kidehen/status/884052454295445505 Symbolic AI • to represent knowledge about world explicitly using some formal knowledge representation language • to derive new knowledge using reasoning system
  • 7. a technology used to store complex structured and unstructured information used by a computer system Knowledge-base https://wiki.dbpedia.org/sites/default/files/DBpediaLogoFull.png https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcShCVNMoom6iYblXzxX-NKEx7uHVRygV_YpYAxbAEeEfQXsH8RX https://tech.africa/wp-content/uploads/Google-Knowledge-Graph.jpg • a collection of interlinked descriptions of entities – real- world objects, events, situations or abstract concepts • authoritative sites, such as Wikipedia, CIA World Factbook and Freebase, used by Google to gather data about people, events, animals, events, history and other topics. • 70 billion facts in October 2016 • a project aiming to extract structured content from the information created in the Wikipedia project • available on the World Wide Web • 4.58 million things including 1,445,000 persons, 735,000 places, 411,000 creative works, 241,000 organizations, 251,000 species and 6,000 diseases in the English version of the DBpedia
  • 8. https://lod-cloud.net/ 국립중앙도서관 국가서지LOD 한국시설안전공단 시설물안전정보LOD 국립수목원 생물정보LOD 서울특별시 서울열린데이터광장LOD 한국관광공사 LOD KDATA
  • 9. voice pickup speech recognition conversational AI question answering answering generationnatural language generation speech synthesisvoice output https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcR1ayWgWdf-hL6H96Jbv_v6bB5Bo03O1r_nrG7MLZr7NTh6UQCpiQ http://www.insideronline.org/wp-content/uploads/2016/06/free-speech-icon.gif http://www.iconarchive.com/download/i86459/graphicloads/long-shadow-documents/document-filetype-text.ico https://www.parson-europe.com/images/einzelbilder/PAG_Icons_Wissensmanagement.png https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTMBZDOrULLUcb9UsC12DqFfgL388ACHlykOA2bT03nXqcs2SdAJQ
  • 10. http://kips.or.kr/society/kips/homepage/bbs/557/1235 * **
  • 11. http://kips.or.kr/society/kips/homepage/bbs/557/1235 * **
  • 12. https://s3-torquehhvm-wpengine.netdna-ssl.com/uploads/2017/09/wp-knowledgebase-plugin.png http://www.goeasybd.com/wp-content/uploads/2018/08/TOURISM.jpg Knowledge-base + Tourism
  • 13. https://vignette.wikia.nocookie.net/smurfs/images/7/71/Tourist_Smurf_SV.png/revision/latest?cb=20161016234608 https://www.kisspng.com/png-darwin-cartoon-illustration-australian-travel-cart-163601/preview.html http://www.xmitter.com/img/icons/online_booking_engine.png https://assets.moneymax.ph/blog/ph_PH/wp-content/uploads/2018/08/credit-card-2761073_640.png https://cdn.pixabay.com/photo/2017/10/25/18/10/peer-review-icon-2888794_960_720.png https://ecommerceguide.com/wp-content/uploads/2015/11/synching-social-media.png
  • 14. Hotel companies seeking to optimize revenue management in today’s competitive environment should consider the following: Data integration across enterprise systems, breaking down data silos and opening up RMS(Revenue Management Strategies) to access and process more complex data feeds in a more flexible fashion. Starwood combines data about weather, economic factors and local events to extract insights that help them decide when to launch promotions or how to price offerings. https://upload.wikimedia.org/wikipedia/commons/thumb/5/55/Ernst_%26_Young_logo.svg/220px-Ernst_%26_Young_logo.svg.png https://en.wikipedia.org/wiki/Starwood#/media/File:Starwood_Hotels_and_Resorts_logo.svg
  • 15. • Knowledge-base makes to create semantically-rich links between data from various heterogeneous sources so that both the tourism industry and travelers benefit from the business insights of big data analytics. • Knowledge-base makes data integration smoother for an enhanced management of both internal and external data. https://cdn.wordlift.io/blog/en/wp-content/uploads/sites/3/2016/10/linked-data-knowledge.png
  • 16. 숙박업소 지식베이스 https://www.yanolja.com/hotel/3012015?checkinDate=2019-02-13&checkoutDate=2019-02-13&list=3rdHotel&position=1 * *
  • 17. 2명 숙박할 수 있는 가까운 호텔 좀 알려줘! 2명 숙박할 수 있는 가까운 호텔 좀 알려줘! SELECT ?호텔 WHERE { ?호텔 is-a 호텔 . ?호텔 보유객실 ?객실 . ?객실 기준인원 2명 . ?호텔 nearby (37.493168 127.030014 1 km) } 2명, (127.030014, 37.493168), 호텔 https://m.post.naver.com/viewer/postView.nhn?volumeNo=10127559&memberNo=34646617 https://www.flaticon.com/free-icon/wedding-couple_146447 http://www.ku.ac.ke/ict/images/resources_imgs/knowlwdgebase.png 글*드 강남 코엑스 센터
  • 18. References • IBM and Pebble Beach Company, https://www.ibm.com/sports/pebble-beach • Pebble Beach, https://www.ibm.com/case-studies/e970253f25300f84 • How Artificial Intelligence will impact the Future of Tourism, https://www.youtube.com/watch?v=Osym1I8hIjg • Pebble Beach with Watson, https://www.youtube.com/watch?v=MvNZs_vts8M • Smart tourism, https://en.wikipedia.org/wiki/Smart_tourism • 4 Emerging Trends of Artificial Intelligence in Travel, https://www.newgenapps.com/blog/artificial-intelligence-in-travel-emerging-trends • Number of mobile phone users worldwide from 2015 to 2020 (in billions), https://www.statista.com/statistics/274774/forecast-of-mobile-phone-users-worldwide/ • 8 Ways in Which IoT is Shaping the Future of Travel Industry, https://www.digitaldoughnut.com/articles/2018/january/ways-in-which-iot-is-shaping-the-future-of-travel • Can you hear me now? Far-field voice, https://towardsdatascience.com/can-you-hear-me-now-far-field-voice-475298ae1fd3 • Artificial intelligence, https://en.wikipedia.org/wiki/Artificial_intelligence#Statistical_learning • Artificial Intelligence, https://slideplayer.com/slide/7428478/ • Understanding the difference between Symbolic AI & Non Symbolic AI, https://www.analyticsindiamag.com/understanding-difference-symbolic-ai-non-symbolic-ai/ • A Path-based Relational RDF Database, https://www.researchgate.net/publication/221152559_A_Path-based_Relational_RDF_Database • Knowledge-based systems, https://en.wikipedia.org/wiki/Knowledge-based_systems • Evolution of machine learning, https://www.sas.com/en_us/insights/analytics/machine-learning.html • 인공지능 서비스 누구(NUGU) 기술 소개, http://kips.or.kr/society/kips/homepage/bbs/557/1235 • Knowledge base, https://en.wikipedia.org/wiki/Knowledge_base • What is a Knowledge Graph?, https://www.ontotext.com/knowledgehub/fundamentals/what-is-a-knowledge-graph/ • The Beginner’s Guide to Google’s Knowledge Graph, https://neilpatel.com/blog/the-beginners-guide-to-the-googles-knowledge-graph/ • DBpedia, https://en.wikipedia.org/wiki/DBpedia • Learn about DBpedia - Facts & Figures, https://wiki.dbpedia.org/about/facts-figures • Linked Data Paths To A Smart Tourism Journey, https://www.ontotext.com/linked-data-paths-smart-tourism-journey/
  • 19. Myungjin Lee LiST, Linked Data and Semantic Web Technology Ph.D. / CTO e-Mail : mjlee@LiSTInc.kr Twitter : http://twitter.com/MyungjinLee Facebook : http://www.facebook.com/mjinlee SlideShare : http://www.slideshare.net/onlyjiny/
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