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Jung 2010

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  • 1. Current Issues Of Semantic Web Technologies in Korea 1 Apr. 2010 Hanmin Jung KISTI 소셜 시맨틱 웹 세미나 1 Copyright © 2004-2010, KISTI
  • 2. Presentations (2009) 미래 연구정보 포럼 2009, 2009.12 (대한상공회의소) Korean Semantic Web Conference 2009, 2009.12 (국립중앙도서관) Search Technology Summit 2009, 2009.9 (그랜드 인터콘티넨탈 호텔) 메타데이터표준화포럼 국제세미나, 2009.6 (코엑스 컨퍼런스 센터) 충남대학교 SOREC 연구소 세미나, “Semantic Service and Service Mashup”, 2009.12 KISTI 기술 이전 설명회, “시맨틱 웹 기술 기반 정보 서비스 플랫폼”, 2009.12 KISTI 하반기 간부 리더쉽 교육, “OntoFrame Project”, 2009.12 독일 Wolters Kluwer GmbH 세미나, “Semantic Web Research of KISTI”, 2009.12 독일 München Univ. 세미나, “Semantic Web Research of KISTI”, 2009.11 KAIST 특강, “시맨틱 웹과 미래 인터넷”, 2009.11 중국 ISTIC 세미나, “Semantic Service Platform and Service Mashup”, 2009.10 영국 Southampton Univ. 세미나, “Semantic Service Researches Of DITR”, 2009.10 행정안전부 제2기 미래 ICT 리더 과정, “ICT 신기술 이해”, 2009.10 행정안전부 제2기 최신 ICT 동향 과정, “미래 정보 서비스와 시맨틱 웹”, 2009.9 솔트룩스 세미나, “특허 동향 고찰과 관련 기술 분석”, 2009.9 KERIS 세미나, “Toward Web 3.0”, 2009.8 고려대 협력 워크숍, “시맨틱 서비스 파이프라이닝”, 2009.8 통계청 세미나, “정보 서비스에서의 시맨틱 웹 역할과 활용 방안”, 2009.5 충남대학교 대학원 특강, “시맨틱 웹과 서비스 플랫폼”, 2009.5 행정안전부 제1기 최신 ICT 동향 과정, “미래 정보 서비스와 시맨틱 웹”, 2009.5 충남대학교 특강, “시맨틱 웹을 적용한 정보 서비스”, 2009.5 충남대학교 세미나, “시맨틱 서비스 플랫폼 OntoFrame”, 2009.4 삼성전자 세미나, “전문용어 구축 및 활용”, 2009.4 행정안전부 제1기 미래 ICT 리더 과정, “ICT 신기술 이해 - 시맨틱 웹, 모바일, 차세대 미디어 등 –”, 2009.4 서울대학교 세미나, “국내 시맨틱 웹 시장 동향 및 온토프레임 소개”, 2009.4 배재대학교 세미나, “차세대 인터넷 기술”, 2009.4 한국정보사회진흥원 세미나, “온톨로지, 시맨틱 웹의 이해와 적용”, 2009.4 KISTEP 세미나, “미래 검색 동향과 시맨틱 플랫폼의 역할”, 2009.3 정보통신연구진흥원 세미나, “미래 검색 동향과 시맨틱 플랫폼의 역할”, 2009.3 한의학 온톨로지 세미나, “언어 자원 구축 – 용어 수집부터 구조 정보 구축까지 –”, 2009.3 국회도서관 설명회, “지능형 입법 지원 시스템 (L-Cube System), 2009.3 한국표준과학연구원 세미나, “시맨틱 서비스 플랫폼 OntoFrame 소개”, 2009.1 소셜 시맨틱 웹 세미나 2 Copyright © 2004-2010, KISTI
  • 3. Presentations (2010) 소셜 시맨틱 웹 세미나, “Current Issues of Semantic Web Technologies in Korea”, 2010.4 NIPA-PS협의체 세미나, “An Insight into Future Information Services”, 2010.3 솔트룩스 세미나, “Benchmarking Semantic Repositories”, 2010.3 기술사업화정보실 세미나, “Semantic Web Research @ KISTI”, 2010.2 국사편찬위원회 세미나, “Understanding Semantic Web Technologies with Use Cases”, 2010.2 국민권익위원회 세미나, “Use Cases of KISTI”, 2010.2 한국표준과학연구원 세미나, “시맨틱 웹 기술을 이용한 참조표준 온라인 보급 활성화 방안”, 2010.1 소셜 시맨틱 웹 세미나 3 Copyright © 2004-2010, KISTI
  • 4. Trend Reports NIPA 주간기술동향 트리플 레파지토리 벤치마킹 (Vol.1439) 차세대 IT 기기와 HCI 기술 동향 전망 (Vol.1435) 시맨틱 검색 기술 동향 (Vol.1431) 시맨틱 웹 국내 특허 동향 (Vol.1420) 감성 분석과 브랜드 모니터링 기술 동향 (Vol.1396) 시맨틱 웹이 경제⋅사회에 미치는 영향 (Vol.1372) 웹 매핑 서비스 비교 분석 (Vol.1352) 시맨틱 웹 2.0 기술 동향 (Vol.1344) 국내 포털 검색 시장 및 특허 동향 (Vol.1341) Open API 기술 동향 (Vol.1296) 엔터프라이즈 검색 기술 동향 (Vol.1276) 전자상거래 검색 기술 동향 (Vol.1273) 시맨틱 웹 포털 기술 동향 (Vol.1264) 기타 동향 분석 보고서 미래의 인터넷을 만드는 핵심기술, 시맨틱 웹 – 월간 웹 (2010년 1월호) 시맨틱 웹 – 2009 국방정보기술 조사서 웹 2.0의 개념과 의의 – KERIS@ Vol.2 미래 정보 사회와 시맨틱 웹 기술 – 디지털행정 (녹색 정보화 특집, 제 113호) 시맨틱 웹 서비스 – KERIS 이슈리포트 (2008-22) 시맨틱 웹 기반 플랫폼상에서의 웹 2.0 활용 서비스 – 정보처리학회지 Vol.14 시맨틱 웹 포털 해외 사례– 지식정보인프라지 Vol.26 소셜 시맨틱 웹 세미나 4 Copyright © 2004-2010, KISTI
  • 5. Advisory Activities (2009-2010) 유관 사업 자문 KAIST: 국가 IT 온톨로지 인프라 구축 사업 한국한의학연구원: 온톨로지 기반 한의학 지능형 정보체계 연구 사업 안보경영연구원: 지능형 통합검색과 품질관리 기능을 향상시킨 군수목록정보체계 아키텍쳐링 연구 사업 정보통신산업진흥원: IT 통계분석 및 동향분석 사업 솔트룩스: 오픈이노베이션 타킷 발견엔진 연구 개발 사업 탑쿼드란트코리아: u-City 서비스용 개방형 SW 플랫폼 개발 사업 선도소프트: 산재예방 통합정보시스템 정보화 전략계획 수립방안에 관한 연구 사업 네오플러스: 표준화 활동 지원 및 관리시스템 구축 사업 DAUM: 디지털 문화콘텐츠 융⋅복합 서비스를 위한 시맨틱 웹 매쉬업 플랫폼 기술 개발 사업 소셜 시맨틱 웹 세미나 5 Copyright © 2004-2010, KISTI
  • 6. 소셜 시맨틱 웹 세미나 6 Copyright © 2004-2010, KISTI
  • 7. 소셜 시맨틱 웹 세미나 7 Copyright © 2004-2010, KISTI
  • 8. DB vs. Ontology Portability & Connectibility Legacy DB For Storing & Managing RDF Triples For Service Planning Services Defining Concepts Ontology Instances Exploiting Relations Ontology Schema 소셜 시맨틱 웹 세미나 8 Copyright © 2004-2010, KISTI
  • 9. Ontologies Modeled by KISTI 소셜 시맨틱 웹 세미나 9 Copyright © 2004-2010, KISTI
  • 10. Ontology Engineering Key Activities Understand business objectives Understand people Understand processes and systems Understand technologies Understand contents Wlodarczyk, “Implementing Semantic Search in the Enterprise” 소셜 시맨틱 웹 세미나 10 Copyright © 2004-2010, KISTI
  • 11. 소셜 시맨틱 웹 세미나 11 Copyright © 2004-2010, KISTI
  • 12. Internet of Things Embracing Web 3.0 “We could use Semantic Web technologies’ representational power to describe things in the real world. One view is that the physical objects will become Web-accessible in that we will be able to represent them via metadata. … Describing physical things will expand our scope beyond the current Web.” by Ora Lassila & James Hendler 소셜 시맨틱 웹 세미나 12 Copyright © 2004-2010, KISTI
  • 13. Linking Data of Real World Semantic Web is rapidly becoming real through evolutionary step in leading the Web to its potential 소셜 시맨틱 웹 세미나 13 Copyright © 2004-2010, KISTI
  • 14. Linking Data of Real World Meaning is learned “inferentially” from a body of data Tim O’Reilly and John Battelle, “Web Squared: Web 2.0 Five Years On”, 2009. 소셜 시맨틱 웹 세미나 14 Copyright © 2004-2010, KISTI
  • 15. LOD Project W3C Linking Open Data Community Project Aims at making data freely available to everyone Extends the Web with a data commons By publishing various open data sets as RDF on the Web By setting RDF links between data items from different data sources Opens the (meta)data silos and get rid of repository-centric mindset Publishes (meta)data of public interest on the Web In a way that other applications can access and interpret the data Using common Web technologies http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData/ Bernhard Haslhofer, “Linked Data Tutorial”, 2009. 소셜 시맨틱 웹 세미나 15 Copyright © 2004-2010, KISTI
  • 16. LOD Project W3C Linking Open Data Community Project over 500 million RDF triples (2007.5) http://blogs.sun.com/bblfish/resource/2007/LinkingOpenData.png 소셜 시맨틱 웹 세미나 16 Copyright © 2004-2010, KISTI
  • 17. LOD Project W3C Linking Open Data Community Project over 2 billion RDF triples (2008.4) Available in RDF and SVG (Scalable Vector Graphics) versions KISTI OntoFrame 2007 Data Set http://richard.cyganiak.de/2007/10/lod/ 소셜 시맨틱 웹 세미나 17 Copyright © 2004-2010, KISTI
  • 18. LOD Project W3C Linking Open Data Community Project over 4.5 billion RDF triples (2009.3) http://www4.wiwiss.fu-berlin.de/bizer/pub/lod-datasets_2009-03-27_colored.png 소셜 시맨틱 웹 세미나 18 Copyright © 2004-2010, KISTI
  • 19. LOD Project W3C Linking Open Data Community Project over 13.1 billion RDF triples, around 142 millions of links (2009.11) http://esw.w3.org/topic/SweoIG/TaskForces/CommunityProjects/LinkingOpenData/ 소셜 시맨틱 웹 세미나 19 Copyright © 2004-2010, KISTI
  • 20. LOD Project Data.gov A product of Obama’s Open Government Initiative project Launched in late May 2009 by the Federal CIO, Vivek Kudra Aims to increase public access to high value, machine readable datasets generated by the Executive Branch of the Federal Government (Over 100 agencies) Major sources of dataset (2009-06-24) Environmental Protection Agency (315) Department of Defense (122) Centers for Medicare and Medicaid Services (108) Department of Health and Human Services (87) Department of Homeland Security (43) Department of the Treasury (37) Department of the Interior (35) US Bureau of Labor Statistics (35) Department of Labor (35) … http://internet.suite101.com/article.cfm/datagov_provides_showcase_for_public_data http://data-gov.tw.rpi.edu/wiki/What%27s_in_data.gov 소셜 시맨틱 웹 세미나 20 Copyright © 2004-2010, KISTI
  • 21. LOD Project Data.gov.uk Prime Minister Gordon Brown appointed Sir Tim and Professor Nigel Shadbolt to open up the official data to the general public (2009.6) Teamed up with Stephen Trimms, Minister for Digital Britain More than 2,500 sets of data from across government including information about house prices, local amenities and services, and access to local hospitals (2010.1) http://www.dailymail.co.uk/sciencetech/article-1244930/Data-gov-uk-Public-website-offering-open-access-Government-data-launched-internet-inventor.html 소셜 시맨틱 웹 세미나 21 Copyright © 2004-2010, KISTI
  • 22. LOD Project Data.gov.uk Demos 소셜 시맨틱 웹 세미나 22 Copyright © 2004-2010, KISTI
  • 23. LOD Project Data.gov.uk Demos 소셜 시맨틱 웹 세미나 23 Copyright © 2004-2010, KISTI
  • 24. LOD Project URI Aliases URIs that refer to the same real-world objects E.g. http://dbpedia.org/resource/Berlin (for Berlin in DBpedia) E.g. http://sws.geonames.org/2950159 (for Berlin in Geonames) Information providers can set owl:sameAs links to URI aliases they know about Resolution of Data Conflicts in Data Fusion Choosing a value in situations where multiple sources provide different values for the same property of an object Christian Bizer, Tom Heath, and Tim Berners-Lee, “Linked Data – The Story So Far”, 2009. 소셜 시맨틱 웹 세미나 24 Copyright © 2004-2010, KISTI
  • 25. Finding Coreferences – Sindice & <sameAs> Interlinking the Web of Data 소셜 시맨틱 웹 세미나 25 Copyright © 2004-2010, KISTI
  • 26. Finding Coreferences – Object Coref in Falcons Bootstrapping Object Coreference Service Input URI 소셜 시맨틱 웹 세미나 26 Copyright © 2004-2010, KISTI
  • 27. LOD Project Government Data Reasons to put online Increasing citizen awareness of government functions to enable greater accountability Contributing valuable information about the world Enabling the government, the country, and the world to function more efficiently Tim Berners-Lee, “Putting Government Data Online”, 2009. 소셜 시맨틱 웹 세미나 27 Copyright © 2004-2010, KISTI
  • 28. 소셜 시맨틱 웹 세미나 28 Copyright © 2004-2010, KISTI
  • 29. Semantic Repository Reasoning P (Precondition), R (Rule), C (Conclusion) Deduction: P + R → C (for forward-chaining) Induction: P + C → R Abduction: C + R → P (for backward-chaining) E.g. “If man is mortal (R) and Socrates is a man (P), then Socrates is mortal (C)” S. Lee, “Research Trends on Reasoning Technologies”, 2010. 소셜 시맨틱 웹 세미나 29 Copyright © 2004-2010, KISTI
  • 30. Semantic Repository Trends on Reasoning (2009) S. Lee, “Research Trends on Reasoning Technologies”, 2010. 소셜 시맨틱 웹 세미나 30 Copyright © 2004-2010, KISTI
  • 31. Semantic Repository Trends on Reasoning (2008~2009) 77 oral/poster/demo/PhD/workshop papers in ESWC & ISWC conferences S. Lee, “Research Trends on Reasoning Technologies”, 2010. 소셜 시맨틱 웹 세미나 31 Copyright © 2004-2010, KISTI
  • 32. Semantic Repository Reasoning Standard reasoning DL-based Rule-based Hybrid (e.g. DL for Tbox, Rule for Abox) Non-standard reasoning Inconsistency handling Uncertainty reasoning: probabilistic/fuzzy Inductive reasoning: clustering Justification finding: exploration of entailments Approximate reasoning: scarifying for soundness/completeness for efficiency Distributed reasoning: on multiple ontologies Parallel reasoning: like multi-threading Stream reasoning: on rapidly changing information S. Lee, “Research Trends on Reasoning Technologies”, 2010. 소셜 시맨틱 웹 세미나 32 Copyright © 2004-2010, KISTI
  • 33. Semantic Repository Semantic Repository Combines characteristics of DBMS and inference engines Uses ontologies as semantic schemata, which allows them to automatically reason about the data Holds, interpret, and serve requests from users Benchmarking Points Data loading (usually includes inference) Query evaluation Data modification Performance Dimensions Scale (in terms of RDF triples) Schema and data complexity Hardware and software setup A. Kiryakov, “Semantic Repositories - Performance factors and design choices”, 2010 소셜 시맨틱 웹 세미나 33 Copyright © 2004-2010, KISTI
  • 34. Semantic Repository Full-cycle Benchmarking Loading input RDF triples from the storage system Parsing the RDF files Indexing and storing the triples Forward-chaining and materialization (optional) Query parsing Query optimization (optional for query re-writing) Query evaluation Backward-chaining (optional) Fetching of the results (post-processing) A. Kiryakov, “Semantic Repositories - Performance factors and design choices”, 2010. 소셜 시맨틱 웹 세미나 34 Copyright © 2004-2010, KISTI
  • 35. OntoFrame – Reasoning 소셜 시맨틱 웹 세미나 35 Copyright © 2004-2010, KISTI
  • 36. Details 소셜 시맨틱 웹 세미나 36 Copyright © 2004-2010, KISTI
  • 37. 소셜 시맨틱 웹 세미나 37 Copyright © 2004-2010, KISTI
  • 38. Semantic … Service Identity Resolution Named-entity Recognition Ontology Modeling Question Answering Semantic Web-based Service ≠ Semantic Service Reasoning Natural Language Interface (SPARQL) Query Interface Information Extraction 소셜 시맨틱 웹 세미나 38 Copyright © 2004-2010, KISTI
  • 39. Semantic … Search Inferential Finding Concept Matching Semantic Web-based Search ≠ Semantic Search Exploratory Session 소셜 시맨틱 웹 세미나 39 Copyright © 2004-2010, KISTI
  • 40. Semantic Search Definition “Semantic search uses language processing to assess the meaning of contents and the meaning of search queries to return more relevant results.” by Paul Wlodarczyk (Early & Associates) Requires technologies To disambiguate search queries (e.g. named entity recognition, WSD) To map search queries to contents (e.g. information extraction) To refine meaning of search queries (e.g. clustering, relevant term search) 소셜 시맨틱 웹 세미나 40 Copyright © 2004-2010, KISTI
  • 41. Semantic Search Engines Evri 소셜 시맨틱 웹 세미나 41 Copyright © 2004-2010, KISTI
  • 42. Semantic Search Engines Nate Semantic Search 소셜 시맨틱 웹 세미나 42 Copyright © 2004-2010, KISTI
  • 43. Semantic Search Engines Nate Semantic Search 소셜 시맨틱 웹 세미나 43 Copyright © 2004-2010, KISTI
  • 44. Semantic Search Engines Naver Lab Movie Search 소셜 시맨틱 웹 세미나 44 Copyright © 2004-2010, KISTI
  • 45. Application Scopes of Natural Language Processing http://www.ukp.tu-darmstadt.de/fileadmin/user_upload/Group_UKP/e-learning2.0qa_sental_small_0.png http://www.monrai.com/products/cypher/img/ad-framework.gif 소셜 시맨틱 웹 세미나 45 Copyright © 2004-2010, KISTI
  • 46. 소셜 시맨틱 웹 세미나 46 Copyright © 2004-2010, KISTI
  • 47. Usability Even the tiniest amount of empirical facts (2 users) vastly improves the probability of making correct UI design decisions Jakob Nielsen’s Alertbox, “Guesses vs. Data as Basis for Design Recommendations”, 2009. 소셜 시맨틱 웹 세미나 47 Copyright © 2004-2010, KISTI
  • 48. Usability Unless your site meets their expectations and can be understood immediately, They’ll beat a fast retreat back to the sites they already know. Jakob Nielsen’s Alertbox, “Guesses vs. Data as Basis for Design Recommendations”, 2009. 소셜 시맨틱 웹 세미나 48 Copyright © 2004-2010, KISTI
  • 49. Usability Content Owners’ Subjective Opinions “Yeah, see, I don’t like that.” “I wouldn’t click there, and so neither will they.” “Oh, they’ll know what that means, even if you don’t.” Jakob Nielsen, “Building Respect for Usability Expertise”, 2009. 소셜 시맨틱 웹 세미나 49 Copyright © 2004-2010, KISTI
  • 50. Usability How Projects Really Work http://www.projectcartoon.com/cartoon/1 소셜 시맨틱 웹 세미나 50 Copyright © 2004-2010, KISTI
  • 51. Usability Bad Usability Is Like a Leaky Pipe http://www.90percentofeverything.com/wp-content/uploads/2006/11/bad_usability_is_like_a_leaky_pipe.jpg 소셜 시맨틱 웹 세미나 51 Copyright © 2004-2010, KISTI
  • 52. Usability Organizational inertia Usability is about humans, not computers Limitations of the human mind Jakob Nielsen’s Alertbox, “Progress in Usability: Fast or Slow?”, 2010. 소셜 시맨틱 웹 세미나 52 Copyright © 2004-2010, KISTI
  • 53. 소셜 시맨틱 웹 세미나 53 Copyright © 2004-2010, KISTI
  • 54. Toward Web 3.0 Recommendation & Personalization One-sided recommendation → collaborative recommendation → contextual recommendation “We’ll have a web that knows what we want and when we want it.” by Jemina Kiss (writer of UK’s Guardian newspaper) 소셜 시맨틱 웹 세미나 54 Copyright © 2004-2010, KISTI
  • 55. Wifi Positioning System New York City http://www.linuxfordevices.com/files/misc/nyc-wifi-points.jpg 소셜 시맨틱 웹 세미나 55 Copyright © 2004-2010, KISTI
  • 56. Recommendation & Personalization Agents SNS Sensors, recognizers Where to adopt Semantic Web technologies 소셜 시맨틱 웹 세미나 56 Copyright © 2004-2010, KISTI
  • 57. 소셜 시맨틱 웹 세미나 57 Copyright © 2004-2010, KISTI
  • 58. Top 10 Predictions (1) Worldwide Information Access, Analysis, and Management Software 2010 (IDC) Information in Context Prediction 1: Experiments in Context and User-Aware Filters Will Increase the Relevance and Usefulness of the Information That Is Retrieved; Location, Device, Task, Job Title, or Personal Interests Will All Provide Clues Prediction 2: Social Graphs Derived from Social Networks Will Improve Understanding of Organizational Structure and Will Supply Recommendations, Filter Search Results and Content Streams, or Find Experts Pervasive Business Intelligence and Analytics Prediction 3: Data Generated from Transactions, Events, Sensors, Conversations, Purchases, and Social Networks Will Drive Predictive Analysis and Improved Decision-Making Processes Prediction 4: New SaaS Offerings for BI, Analytics, and Data Provided as a Service Will Address the Lack of Analytics Expertise at Many Organizations Prediction 5: Mining for Meaning Will Rise in Importance; Text Analytics Will Be Embedded in BI Systems to Merge Content with Data; Other Applications That Require a High Degree of User Interaction Will Add Text Analytics, Search, and Multilingual Features 소셜 시맨틱 웹 세미나 58 Copyright © 2004-2010, KISTI
  • 59. Top 10 Predictions (2) Worldwide Information Access, Analysis, and Management Software 2010 (IDC) Information Overload and Risk Avoidance Spur Information and Application Integration Prediction 6: Intelligent Workspaces Will Emerge and Quickly Gain Market Share Prediction 7: Decision Management Systems Will Emerge to Extend Information Access Systems to All Steps in the Decision-Making Process Change, Disruption, and New Opportunities Prediction 8: Demand for Integrated Platforms to Support eCommerce Will Reemerge Prediction 9: Software Delivery and Licensing Models Will Diversify to Include More SaaS Delivery, More Appliances, and More Open Source Software Prediction 10: Chaos in the Workplace Will Increase as Business Users Either Bring Their Own Software Tools to Work or Take Charge of Software Purchases 소셜 시맨틱 웹 세미나 59 Copyright © 2004-2010, KISTI
  • 60. Work Program 2011-2012 2010 (European Commission) Challenge 1: Pervasive and Trusted Network and Service Infrastructures Challenge 2: Cognitive Systems and Robotics Challenge 3: Alternative Paths to Components and Systems Challenge 4: Technologies for Digital Content and Languages Challenge 5: ICT for Health, Ageing Well, Inclusion and Governance Challenge 6: ICT for a low carbon economy Challenge 7: ICT for the Enterprise and Manufacturing Challenge 8: ICT for Learning and Access to Cultural Resources 소셜 시맨틱 웹 세미나 60 Copyright © 2004-2010, KISTI
  • 61. Work Program 2011-2012 2010 (European Commission) Challenge 1: Pervasive and Trusted Network and Service Infrastructures Objective ICT-2011.1.1: Future Networks Objective ICT-2011.1.2: Cloud Computing, Internet of Services and Advanced Software Engineering Objective ICT-2011.1.3: Internet-connected objects Objective ICT-2011.1.4: Trustworthy ICT Objective ICT-2011.1.5: Networked Media and Search Systems Objective ICT-2011.1.6: Future Internet Research and Experimentation (FIRE) Objective FI.ICT-2011.1.7: Technology foundation: Future Internet Core Platform Objective FI.ICT-2011.1.8: Use Case scenarios and pilots Objective FI.ICT-2011.1.9: Capacity Building and Infrastructure Support Objective FI.ICT-2011.1.10: Program Management and Support 소셜 시맨틱 웹 세미나 61 Copyright © 2004-2010, KISTI
  • 62. Work Program 2011-2012 2010 (European Commission) Challenge 4: Technologies for Digital Content and Languages Objective ICT-2011.4.1: SME initiative on Digital Content and Languages Objective ICT-2011.4.2: Language Technologies Multilingual content processing Information access and mining Natural spoken interaction Developing joint plans, methods and services (speech & natural language) Objective ICT-2011.4.3: Digital Preservation Objective ICT-2011.4.4: Intelligent Information Management 소셜 시맨틱 웹 세미나 62 Copyright © 2004-2010, KISTI
  • 63. 감사합니다! jhm@kisti.re.kr 소셜 시맨틱 웹 세미나 63 Copyright © 2004-2010, KISTI
  • 64. 감사합니다! jhm@kisti.re.kr 소셜 시맨틱 웹 세미나 64 Copyright © 2004-2010, KISTI
  • 65. 조직 외부에서 누군가 여러분의 문제에 대해 답하고, 해결해주며, 현재의 기회를 잘 활용하는 방법을 알고 있다면, 그들을 찾아내 생산적으로 협업할 길을 찾기만 하면 된다. by A.G. Lafley (P&G CEO) 감사합니다! jhm@kisti.re.kr 소셜 시맨틱 웹 세미나 65 Copyright © 2004-2010, KISTI