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Webinar: Metadata Enrichment in Publishing

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The slide deck from the October 29, 2015 webinar "Metadata Enrichment in Publishing: Boosting Productivity and Increasing User Engagement" presented by Ilian Uzunov and Georgi Georgiev.

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Webinar: Metadata Enrichment in Publishing

  1. 1. Metadata Enrichment in Publishing: Boosting Productivity and Increasing User Engagement Ontotext webinar series – 29th of October 2015 11am ET | 10am CT |8am PT | 1500 UTC
  2. 2. Agenda • Company info • Metadata challenges • Ontotext approach to metadata enrichment – Dr. Georgiev • Live demos • Wrap up + QnA Oct 2015Metadata Enrichment in Publishing 2
  3. 3. Company essentials • One-stop shop for semantic technology − Text Analytics + Content Enrichment + Search + Graph Database Engine − Over 400 person-years in R&D • Started in year 2000 − As R&D lab within Sirma – the biggest Bulgarian software company • Got spun-off and took VC investment in 2008 • 70 staff, growing revenue, profitable − HQ in Sofia, Bulgaria, offices in London and NYC Oct 2015Metadata Enrichment in Publishing 3
  4. 4. Company essentials Why? enable better search, analytics and content delivery What? data and content management technology How? semantic analysis of text, NoSQL graph database Best for: content publishing and information discovery Oct 2015Metadata Enrichment in Publishing 4
  5. 5. Clients (selection) Oct 2015Metadata Enrichment in Publishing 5 Major financial Information agency Major business and legal Information agency
  6. 6. What others are saying about metadata… • "Metadata Matters" Bloomberg white paper, 2014 “Metadata was once purely the domain of the tech team, today it affects everyone in a media and publishing organizations—from editorial team members to business leaders." • John O'Donovan, Former CTO of Financial Times "Everyone forgets about metadata. All your assets are useless to you unless you have metadata – your archive is full of stuff that is of no value because you can’t find it and don’t know what it’s about.” • A manifesto on metadata, Thad Mcllroy The only way to make publishing's great content discoverable, is "via rich metadata linked into smart search systems." Oct 2015Metadata Enrichment in Publishing 6
  7. 7. Types of metadata •Structural metadata •Technical metadata •Descriptive metadata •Administrative metadata •Rights metadata •Commercial metadata Oct 2015Metadata Enrichment in Publishing 7
  8. 8. Technical metadata • Examples of enrichment of technical metadata “Tagasauris saw the potential for a semantic engine like GraphDB to add value and intelligence to their tagging services.” Oct 2015Metadata Enrichment in Publishing 8
  9. 9. Descriptive metadata • Examples of enrichment of descriptive metadata “With semantic metadata you can describe your content in terms of the locations, people, organizations, brands, etc that the content is about.” Oct 2015Metadata Enrichment in Publishing 9
  10. 10. The risk of being negligent to your metadata “The failure to adequately account for each type of metadata can affect a publishing company’s ability to efficiently create, store, find, access and publish content of all types!” "Metadata Matters" Bloomberg white paper, 2014 Oct 2015Metadata Enrichment in Publishing 10
  11. 11. Why do we need to care more about metadata? •Мetadata drives content organization, workflow optimization and automation •It’s economically smarter to tie assets together throughout the supply chain with metadata Oct 2015Metadata Enrichment in Publishing 11
  12. 12. Typical publishing workflow Oct 2015Metadata Enrichment in Publishing 12
  13. 13. Semantic publishing workflow Oct 2015Metadata Enrichment in Publishing 13
  14. 14. Why do we need to care more about metadata? •A strong metadata system can power centralized searches, helping find assets across data silos •If an asset can be easily found, it can be reused and repurposed more easily Oct 2015Metadata Enrichment in Publishing 14
  15. 15. Easily discover all your content assets Oct 2015Metadata Enrichment in Publishing 15
  16. 16. Metadata can empower automation • Many publishers still rely on big teams of editors to manage their digital offerings while at the same time • A single editor could aggregate all content that relates to particular topic and with appropriate metadata tagging that could happen automatically Oct 2015Metadata Enrichment in Publishing 16
  17. 17. Use case: BBC • Goals − Create a dynamic semantic publishing platform that assembles web pages on- the-fly using a variety of data sources − Deliver highly relevant data to web site visitors with sub-second response • Challenges − BBC journalists author and publish content which is then statistically rendered. The costs and time to do this were high − Diverse content was difficult to navigate, content re-use was not flexible Oct 2015Metadata Enrichment in Publishing 17 "The goal is to be able to more easily and accurately aggregate content, find it and share it across many sources. From these simple relationships and building blocks you can dynamically build up incredibly rich sites and navigation on any platform." John O’Donovan, Chief Technical Architect, BBC
  18. 18. Metadata can greatly enhance discoverability • United metadata across multiple data silos can provide a universal search solution for editors looking for specific content – internal usage and search • Publishers need to take full advantage of traffic from search to better expose and potentially monetize their content Oct 2015Metadata Enrichment in Publishing 18
  19. 19. Use case: EuroMoney Oct 2015Metadata Enrichment in Publishing 19 • Goals − Create a horizontal platform to serve 100 different publications − Platform which would include the latest authoring, storing, and delivery technologies including, semantic annotation, search and a triple store repository • Challenges − Multiple domains covered − Sophisticated content analytics including relation, template and scenario extraction
  20. 20. Metadata can drive user engagement •Recommendation engines also rely on metadata to suggest content to users •So, ultimately, the better structured and more accurate the metadata, the more likely recommended content to be highly relevant Oct 2015Metadata Enrichment in Publishing 20
  21. 21. Use case: Financial Times Oct 2015Metadata Enrichment in Publishing 21 • Goals − Create a horizontal platform for both data and content based on semantics and serve all functionality through this platform • Challenges − Critical part of FT.COM − Personalized recommendation based on user behavior and semantic context (Related Reads)
  22. 22. Ontotext value proposition • Make Text and Data Tango Together! − Today there is an artificial divide between text and data − Semantic technology removes the divide and brings them together • We interlink text and data to unveil their meaning − Large knowledge graphs help text-mining! − Interlinking text and data allows us to add context and meaning to both • We deliver unmatched search and exploration − Across all sorts of data and at a fraction of the cost of alternative approaches Oct 2015Metadata Enrichment in Publishing 22
  23. 23. ONTOTEXT Technology: Analyzing Text Oct 2015Metadata Enrichment in Publishing 23 • Full spectrum of NLP capabilities • Semantic indexing − Tag references with entity IDs − Generate semantic metadata descriptions of documents − Store metadata in GraphDB
  24. 24. ONTOTEXT Technology: Interlinking Text and Data Oct 2015Metadata Enrichment in Publishing 24 • Use large knowledge graphs for text analysis • Semantic annotation and search − Combine structured database queries with full-text search and inference We make sense of text and data by linking and interpreting them together
  25. 25. Methodology Oct 2015Metadata Enrichment in Publishing 25
  26. 26. Methodology Oct 2015Metadata Enrichment in Publishing 26
  27. 27. Methodology Oct 2015Metadata Enrichment in Publishing 27
  28. 28. Example KB for 50 daily publications Oct 2015Metadata Enrichment in Publishing 28
  29. 29. Methodology Oct 2015Metadata Enrichment in Publishing 29
  30. 30. Design of Machine Learning Pipeline Oct 2015Metadata Enrichment in Publishing 30
  31. 31. Continuous Adaptation Oct 2015Metadata Enrichment in Publishing #31
  32. 32. Examples: Semantic Content Enrichment Oct 2015Metadata Enrichment in Publishing 32
  33. 33. Examples: Semantic Content Enrichment (live) Oct 2015Metadata Enrichment in Publishing 33
  34. 34. Examples: Faceted Search-Co-occurrence (live) Oct 2015Metadata Enrichment in Publishing 34
  35. 35. Examples: Key Entities & Trends (live) Oct 2015Metadata Enrichment in Publishing 35
  36. 36. Proven in Publishing and Other Sectors • Application: Content production and delivery − Helping for: authoring, enrichment, presentation, re-purposing, personalized recommendation • Application: Information discovery − Powerful semantic enterprise search for applications like regulation compliance and drug safety • Valuable collection of use cases: 10+ high-profile projects − Business news: FT, Bloomberg, Euromoney − Scientific publishing: John Willie & Sons, Oxford University Press, IET − Media & content publishers: BBC, DK, Getty, Disney, ... Oct 2015Metadata Enrichment in Publishing 36
  37. 37. Semantic News Publishing Solution Oct 2015Metadata Enrichment in Publishing 37 • They have tons of great content − That is expensive to manage and reuse • But struggle to engage readers − Hard to compete with social networks and other online and mobile channels • Solved by Ontotext − Dynamic topic aggregation & feed generation − Personalized recommendations
  38. 38. Scientific Publishing Solution Oct 2015Metadata Enrichment in Publishing 38 • They have tons of legacy static content − That is expensive to manage and reuse • And struggle to monetize their content − Hard to compete with platforms providers and open access resources • Solved by Ontotext − Smarter search and recommendations − Taxonomy, Thesauri, Vocabulary enrichment − Dynamic content aggregation
  39. 39. Personalized Learning Solution Oct 2015Metadata Enrichment in Publishing 39 • They have tons of static content − That is expensive to manage and reuse • And struggle to engage learners and educators − Hard to compete with the ed-tech companies and free e-learning resources • Solved by Ontotext − Mapping of learning resources to curricula − Dynamic content aggregation − Personalized learning
  40. 40. Wrap up • Unique Technology Portfolio − Top notch RDF graph database and text-mining − One-stop shop for content enrichment and metadata management • End-to-end solution for Media and Publishing − Authoring, curation and publishing through adaptive text-mining • Proven to Deliver – we run FT.COM and BBC.CO.UK/SPORT • Stable, Sustainable and Growing Company Oct 2015Metadata Enrichment in Publishing 40
  41. 41. Thank you! Experience the technology with NOW: Semantic News Portal http://now.ontotext.com Try out our Semantic tagging service http://tag.ontotext.com Learn more at our website or simply get in touch info@ontotext.com, @ontotext Oct 2015Metadata Enrichment in Publishing 41

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