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PROF. VINCENT WADE, DIRECTOR CNGLTrinity College Dublin
Objective• To Examine the Possible influences andFuture Solutions for Global ContentAsk the Questions• Revolution or Evolu...
3
• Commoditisation of Content and its localisation– Business Model on ‘cost per word’ rather than value– Constant optimisat...
5
But Localisation is just a component in theContent Value Chain– Upstream dependencies– Down stream implications6
MultiLingual WebEnglish only 27% of all languages on Internet in 2010Facebook 50M 2007 600M 2010 …. 1L 2007 77L 2010Twitte...
8
What if content could be intelligent?9
10As Velocity Climbs…– Comprehension FallsAs Variety Climbs…– Consumability FallsAs Volume Climbs…– Findability Falls
12Build and Sustain world leading centre of excellence inGlobal Intelligent Content and revolutionise technology forthe gl...
ScientificExcellenceProductiveCollaborationIMPACTIndustryAcademiaBasic +Applied Societal +CommercialAgile Ambitious
CNGL I ACHIEVEMENTS~€48mR&D InvestmentOver 5 years~150People15+FP7 Proj.4Licenses5 (3)Spinouts10Sponsors38IDFs/SDFs9Pat. A...
15INTEL
PAPER: Computational Stylometry: Whos in a Play(Vogel & Lynch, 2008)PATENT: A Data Processing System and Methodfor Assessi...
Personalisation in the wild: providing personalisationacross semantic, social and open-web resources.(Steichen, et al 2009...
19As Velocity Climbs…– Comprehension FallsAs Variety Climbs…– Consumability FallsAs Volume Climbs…– Findability Falls
20
Where the contentproactively enables itsOwn Discovery,Analysis, Transformation& DeliveryBy embedding newlevels of knowledg...
• Understand +In Perspective• Discover + Relate +Link• With regards toLanguage + Culture• Adapting to Individualand contex...
ReconfigurableIntelligentContent23AdaptableReusableDiscoverableSemanticallyAware
IntelligentContent24AdaptableLinguisticallyTransparentDiscoverableSemanticallyAwareReconfigurable
SemanticallyAwareTuning TextAnalyticsEvent & OpinionExtractionPurpose DrivenCuration
DiscoverableContent AwareMultilingualSearchContextualisationModalityIndependent
LanguageTransparentIntelligent MachineTranslationSocial LocalisationLinguistic &Societal Impact
AdaptableAdaptive SlicingSocial AdaptationAffectivePersonalisation
ReconfigurableDialogueInterfacesDevice SpecificRenderingHuman in the Loop
QuantifiableGlobal IntelligentContentSocial AnalyticsIntegration &Standards
31Example: Global Intelligent Content for Global Customers
33
35
• Model participants/cohorts in customer forums
• Model facial features during spoken interaction
• Infuse speech translation with emotion
CASE STUDIES Global Intelligent Content :Personalisation for Corporate & UserGenerated ContentPROF VINCENT WADE CNGL DIREC...
Problem / Market NeedOne size doesn’t fit all!People have different:• Roles, Needs, Abilities, Preferences,Contexts of use...
1. Personlised Information Portal (automatedpresentation generation)2. Dynamic Personalisation of Activities, Content &Por...
Dynamic Personalisation: Activities,Content, PortalsPersonalised SQL Activities
Key Innovation: Personalized, point-of-need learning•e-Learning content disaggregated into learning objects andmeta-tagged...
Key Innovation: Enhanced SearchCombination of Semantic and Social Searchsearches over all content repositories toreturn re...
Key Innovation: Informal Learning DataAnalytics•Quantitive data (contribution level)•Qualitative data (contribution value)...
Personalisation in Casual Games
• Instantaneous provision of context-appropriateanalysis, translation, (re)composition anddelivery• Dynamic adaptation, pe...
Effective Content Curation, Management andPersonalisationfor Corporate & User Generated ContentPROF VINCENT WADE CNGL DIRE...
Content Curation and Searchfor Corporate & User Generated ContentPROF VINCENT WADE CNGL DIRECTOR,TRINITY COLLEGE DUBLIN
• Automated Generation of Metadatafrom Corporate and User GeneratedContent for usage across the contentvalue chain– Text A...
• Personalised Search• Multilingual Search• Social Search,• Multimodal Search (searchspeech & text based)• MultiModal (spe...
DymamicallyPersonalisedMobile Access &Mobile DeliveryMultimedia &MultiModal (text, video,graphic & speech)Integration of C...
DEMO ofPersonalised MultilingualCustomer Care
60
Personalised MultiLingual Customer Care Portals
New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction
New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction
New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction
New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction
New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction
New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction
New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction
New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction
New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction
New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction
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New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction

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According to CNGL's Prof. Vincent Wade, one of the most significant changes to people’s lives in recent years has been the explosion of content. The volume generated, the accuracy of targeted audience and the means of accessing content via different media and devices is changing continuously. While organisations, communities and individuals are increasingly seeking content and services to be delivered in their own language, according to their needs, preferences and context, corporations are increasingly seeking to leverage content created by users and engage in closer interaction with global customers and communities. This presentation outlines the embedded intelligence for interaction with dynamic global content – i.e. content that can leverage cloud services for advanced analytics, search optimization, translation, localisation, personalisation and interaction across the delivery chain, enabling the aggregation, machine translation and interaction with multilingual user-generated, corporate and open content to satisfy the global customer.

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New Horizons for Global Content: Embedded intelligence for Dynamic Global Content Interaction

  1. 1. PROF. VINCENT WADE, DIRECTOR CNGLTrinity College Dublin
  2. 2. Objective• To Examine the Possible influences andFuture Solutions for Global ContentAsk the Questions• Revolution or Evolution in Global Content ?• What Scientific Challenges for NextGeneration Content ?• How will it impact Business in the Future?2
  3. 3. 3
  4. 4. • Commoditisation of Content and its localisation– Business Model on ‘cost per word’ rather than value– Constant optimisation of worklfow process• Translation/Localistion becoming increasingly‘continuous’ rather than ‘batch’ oriented– Granular & continuous• Increase in Variety of Content– Traditional, multimadia, games based, social media,multimodal, video, ……• Velociity (of Content) :: 4
  5. 5. 5
  6. 6. But Localisation is just a component in theContent Value Chain– Upstream dependencies– Down stream implications6
  7. 7. MultiLingual WebEnglish only 27% of all languages on Internet in 2010Facebook 50M 2007 600M 2010 …. 1L 2007 77L 2010Twitter 55% tweets non-English February 2010The Mobile WebMultiModalMobile2 Billion Web users5+ Billion mobile phonesMultimodal access/interactionsTextSpeechVideoPicturesAudioUser Generated ContentBeginning to outpace professionallyedited contentNew business modelsBusiness IntelligenceCustomer supportCustomer loyaltyChallenge:Noisy data, ungrammatical, spelling,…:“Thank you for the wiki links, do youcompiled adn updated list ?”Diversity of UsersPrior Knowledge &ExpertiseDevice andModalityContext of UseAims and GoalsHistory,Preferences &CultureLanguage& CommunicationStyle
  8. 8. 8
  9. 9. What if content could be intelligent?9
  10. 10. 10As Velocity Climbs…– Comprehension FallsAs Variety Climbs…– Consumability FallsAs Volume Climbs…– Findability Falls
  11. 11. 12Build and Sustain world leading centre of excellence inGlobal Intelligent Content and revolutionise technology forthe global content value chainDeliver significant impact for industry and createcommercialisation benefits for Irish-based enterprises andIrish entrepreneursEmpower people and organisations in Ireland to achieveglobal impact via social and commercial improvements
  12. 12. ScientificExcellenceProductiveCollaborationIMPACTIndustryAcademiaBasic +Applied Societal +CommercialAgile Ambitious
  13. 13. CNGL I ACHIEVEMENTS~€48mR&D InvestmentOver 5 years~150People15+FP7 Proj.4Licenses5 (3)Spinouts10Sponsors38IDFs/SDFs9Pat. App.21Prototypes
  14. 14. 15INTEL
  15. 15. PAPER: Computational Stylometry: Whos in a Play(Vogel & Lynch, 2008)PATENT: A Data Processing System and Methodfor Assessing Quality of a Translation
  16. 16. Personalisation in the wild: providing personalisationacross semantic, social and open-web resources.(Steichen, et al 2009)PATENT: A network system for generating applicationspecific hypermedia content from multiple sources
  17. 17. 19As Velocity Climbs…– Comprehension FallsAs Variety Climbs…– Consumability FallsAs Volume Climbs…– Findability Falls
  18. 18. 20
  19. 19. Where the contentproactively enables itsOwn Discovery,Analysis, Transformation& DeliveryBy embedding newlevels of knowledge andintelligence intothe content21
  20. 20. • Understand +In Perspective• Discover + Relate +Link• With regards toLanguage + Culture• Adapting to Individualand context of use• Considering Right-Time+ Right-Way Delivery22
  21. 21. ReconfigurableIntelligentContent23AdaptableReusableDiscoverableSemanticallyAware
  22. 22. IntelligentContent24AdaptableLinguisticallyTransparentDiscoverableSemanticallyAwareReconfigurable
  23. 23. SemanticallyAwareTuning TextAnalyticsEvent & OpinionExtractionPurpose DrivenCuration
  24. 24. DiscoverableContent AwareMultilingualSearchContextualisationModalityIndependent
  25. 25. LanguageTransparentIntelligent MachineTranslationSocial LocalisationLinguistic &Societal Impact
  26. 26. AdaptableAdaptive SlicingSocial AdaptationAffectivePersonalisation
  27. 27. ReconfigurableDialogueInterfacesDevice SpecificRenderingHuman in the Loop
  28. 28. QuantifiableGlobal IntelligentContentSocial AnalyticsIntegration &Standards
  29. 29. 31Example: Global Intelligent Content for Global Customers
  30. 30. 33
  31. 31. 35
  32. 32. • Model participants/cohorts in customer forums
  33. 33. • Model facial features during spoken interaction
  34. 34. • Infuse speech translation with emotion
  35. 35. CASE STUDIES Global Intelligent Content :Personalisation for Corporate & UserGenerated ContentPROF VINCENT WADE CNGL DIRECTOR,TRINITY COLLEGE DUBLIN
  36. 36. Problem / Market NeedOne size doesn’t fit all!People have different:• Roles, Needs, Abilities, Preferences,Contexts of use, Devices …Technology SolutionBringing the right Content andServices to the end-user• Driven by Strategies, Models,Meta-data & Behaviour• Flexible and configurable• Service based
  37. 37. 1. Personlised Information Portal (automatedpresentation generation)2. Dynamic Personalisation of Activities, Content &Portal Services3. Personalised Corporate Portals for InformalLearning (across Social, Open and CorporateMedia)4. Personalisation in Casual Games
  38. 38. Dynamic Personalisation: Activities,Content, PortalsPersonalised SQL Activities
  39. 39. Key Innovation: Personalized, point-of-need learning•e-Learning content disaggregated into learning objects andmeta-tagged•Recomposed into a Learning Episode tailored to searcher’s rolewithin organisation•Learning Episode also presents searcher with content relatedto their search term which they may not have consideredIncreases the potential reuse of content• 67 Courses (402 topics) from Leadershipdomain• 402 topics tagged to 45 competenciesExample: Delivering a difficult message tagged31 times in different contextsPersonalised Corporate Portal
  40. 40. Key Innovation: Enhanced SearchCombination of Semantic and Social Searchsearches over all content repositories toreturn resources that are:• Context-relevant• Highly rated by community of peersPersonalised Corporate Portal
  41. 41. Key Innovation: Informal Learning DataAnalytics•Quantitive data (contribution level)•Qualitative data (contribution value)•Manager View for 360°Appraisals•Employee View•Updates in real time
  42. 42. Personalisation in Casual Games
  43. 43. • Instantaneous provision of context-appropriateanalysis, translation, (re)composition anddelivery• Dynamic adaptation, personalisation andrecomposition for user empowerment andcontent contextualisation• Enhancement of interaction through multi-modal and multi-device delivery• Integration and optimisation of intelligentcontent processes across the value chain52
  44. 44. Effective Content Curation, Management andPersonalisationfor Corporate & User Generated ContentPROF VINCENT WADE CNGL DIRECTOR,TRINITY COLLEGE DUBLIN
  45. 45. Content Curation and Searchfor Corporate & User Generated ContentPROF VINCENT WADE CNGL DIRECTOR,TRINITY COLLEGE DUBLIN
  46. 46. • Automated Generation of Metadatafrom Corporate and User GeneratedContent for usage across the contentvalue chain– Text Analytics– Entity Extraction– Event Extraction– Sentiment analysis– Metadata Generation– Content Quality Estimation– Data Visualisation 56
  47. 47. • Personalised Search• Multilingual Search• Social Search,• Multimodal Search (searchspeech & text based)• MultiModal (speech based)Interactive Search57• Automated Machine Translation,• Post-Editing Tools, Crowdsourced Translation
  48. 48. DymamicallyPersonalisedMobile Access &Mobile DeliveryMultimedia &MultiModal (text, video,graphic & speech)Integration of Corporate &UGCMultiLingual
  49. 49. DEMO ofPersonalised MultilingualCustomer Care
  50. 50. 60
  51. 51. Personalised MultiLingual Customer Care Portals

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