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SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
SharePoint 2010 Findability
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SharePoint 2010 Findability

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How Smartlogic Semaphore improves Findability in SharePoint 2010, through content enrichment and semantic search enhancement.

How Smartlogic Semaphore improves Findability in SharePoint 2010, through content enrichment and semantic search enhancement.

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  • Dieses Zitat
  • http://bit.ly/gglmYd
  • http://www.ic.nhs.uk/
  • Transcript

    • 1. Metadata and Findability in SharePoint 2010
      Dave Maskell
      European Sales Manager
      dave.maskell@smartlogic.com
    • 2. Smartlogic Semaphore
      Semaphore improves Findability in SharePoint and other applications, through automated content classification and search enhancement.
      Findability: brings people and knowledge together. Enables users to find the information they seek and promotes content to the relevant audience.
    • 3. Customer Benefit Examples
      Internal Knowledge Management
      SharePoint
      Inform/Serve Customers
      Monetise Information
    • 4. Knowledge Management Trends
      Increasing demand for “information about information”
      • Support knowledge workers
      • 5. Records Management
      • 6. Legal (e.g. eDiscovery, Freedom Of Information, Audit)
      Systems consolidation
      • From departmental to enterprise repositories
      Little editorial control
      • People are encouraged/compelled to upload everything
      • 7. No SEO on the intranet
    • Goal
      Knowledge
      Information
      Hidden
      Data
      Unknown
      Knowing What You have
      The British Museum has a collection of 7 million items, of which 50,000 are on display
      US museums have 146 million items, 53% of which are not catalogued
      Surfaced
      Knowledge
      You know where it is
      Value
      Information
      You know it’s somewhere
      Data
      You don’t know it exists
    • 8. Free-Text SearchThe “long tail” problem
      20% of content “wins” 80% of searches
      Free-Text search is a blunt instrument
      Heavy documents float, light ones sink!
      What are the “right questions”?
    • 9. Language and Meaning
      Aboutness- what is it?
      Terminology - what do we call it?
      Ambiguity – what did you mean?
    • 14. Precision and Recall
      When is a Lift not a Lift?
      Poor Precision – “false positives”
      Document mentions Lift once in 100 pages – it is not about Lifts
      Wrong kind of lift – document about “valve lift” systems for cars
      Poor Recall – “hidden knowledge”
      Oops!
    • 15. Investing in Context
      Broader Topics
      Related Topics
      Narrower
      Topics
      Topic-Relevant
      Content
    • 16. Failure of Context
    • 17. The Value of Metadata
      Standardisation and Context
      • Standardise Naming & Context:
      • 18. Preferred Term = Elevator
      • 19. Synonym = Lift
      Taxonomy/Ontology
      Term Set
      Model Metadata
      • Tag Content for “aboutness”
      • 20. Based on weight of evidence
      • 21. Some documents are about Elevators others are about Valve-lift Systems
      Classification
      Enterprise Keywords
      Item Metadata
      Search
      Enhancement
      • Improve Search Recall:
      • 22. “Did you mean elevator”?
      • 23. Improve Search Precision
      • 24. Filter by Metadata
      • 25. Improve Search Recall & Precision:
      • 26. Search by Metadata
      • 27. Guided Discovery
    • SharePoint 2010
      “Metadata 1.0”
    • 28. SharePoint Metadata 1.0Structural attributes: Type, Author, Date etc.
    • 29. SharePoint Metadata 1.0“Aboutness” (Term Store & Keywords)
    • 30. SharePoint Metadata 1.0Column Filters
    • 31. SharePoint Metadata 1.0Free-text search, topic refinement
    • 32. Metadata 1.0 Challenges
      “…many departments and organisations in the public sector arbitrarily pick a convenient high-level term from IPSV* to classify all their web pages just so that they can tick the box…”
      • Human tagging is costly, unenforceable, inconsistent
      • 33. Who tags legacy/imported documents?
      • 34. Changed documents do not get re-tagged
      • 35. Term Set changes make metadata obsolete
      • 36. Untagged or badly-tagged documents are “filtered out” or waste user time/attention
      *IPSV = UK Integrated Public Sector Vocabulary (3,000 terms)
    • 37. Semaphore for
      SharePoint 2010
      Complete, consistent, correct Metadata
      Improved Search Experience
    • 38. Complete, consistent, correct MetadataClassification Requirements
      • Automatic Classification is essential for complete, consistent and correct Metadata.
      • 39. Automatic Classification needs to include a number of capabilities:
      • 40. Quality Classification, not just keyword matching
      • 41. Classification triggered on document creation and update
      • 42. Ability for users to add/delete tags
      • 43. Protect manually tagged documents from reclassification
      • 44. Bulk Classification of libraries
    • Complete, consistent, correct MetadataModel-Driven Classification
      How would YOU decide whether a document is ABOUT Apollo 11?
      Encapsulate this knowledge map in a formal rule
    • 45. Complete, consistent, correct MetadataModel-Driven Classification
    • 46. Complete, consistent, correct MetadataUser Classification
    • 47. Complete, consistent, correct MetadataProtecting User Choices
    • 48. Improved Search Experience“Did you mean?”
    • 49. Improved Search ExperienceSemantic Enhancement
      Metadata Search
      Related Topics
      Recommended Links
    • 50. Improved Search ExperienceRelated Topics – Guided Discovery
    • 51. Solution Architecture
      SharePoint 2010 and SharePoint 2007
      Smartlogic Semaphore
      Content
      Classification
      Term Store
      Management
      Search
      Enhancement
      Other Enterprise Applications?
    • 52. Enterprise-Wide Hunger for Context…
      Enterprise
      Search
      Content
      Management
      Portal
      Infrastructure
      Document
      Management
      ?
      ?
      ?
      ?
      SharePoint
      ?
      Records
      Management
      ?
      Publishing
      Systems
      ?
      Digital
      Asset
      Management
      ?
      ?
      ?
      Process
      Management &
      Workflow
      eDiscovery
    • 53. …requiring an Enterprise Solution
      Enterprise
      Search
      Content
      Management
      Portal
      Infrastructure
      Document
      Management
      Subject
      Geography
      Process
      Metadata
      (Tags)
      Model
      (Ontology)
      SharePoint
      Records
      Management
      Publishing
      Systems
      Digital
      Asset
      Management
      Semaphore EnterpriseSemanticPlatform
      Process
      Management &
      Workflow
      eDiscovery
    • 54. Case Study:
      UK National Health Service
    • 55. Medical Information for PatientsSharePoint with GSA Search
      Topic Filters
      Recommendation
    • 56. Interactive Term Map - Visualisation
    • 57. Interactive Term Map - Visualisation
    • 58. Social Media Content Classification
    • 59. Medical Information for PractitionersFAST ESP across 100+ web sites
    • 60. Conclusions
      The SharePoint 2010 Term Store and Managed Metadata are a first step towards improved Findability.
      To be effective, Metadata must be complete, consistent and correct. This requires automation.
      SharePoint 2010 findability can be further improved through semantic concepts like “did you mean?”, metadata searching and related topic suggestions.
      The same is true for other applications that use unstructured content.
      Smartlogic Semaphore provides an enterprise platform for metadata management and semantic search enhancement.
    • 61. Thank You
      Dave Maskell
      European Sales Manager
      dave.maskell@smartlogic.com

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