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SharePoint site admins leverage search

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SharePoint site admins leverage search

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SharePoint site admins leverage search

  1. 1. Maximizing Search
  2. 2. About me • Julie Boudro • Consultant • MCITP, MCTS, MCT • julieb@cdh.com • 248.554.3176
  3. 3. Why maximize search? • Increase findability of information • Reduce frustration in end users • Increase adoption • Create a new set of tools for rendering content in SharePoint • Way of the future with O365 and Delve
  4. 4. Mechanics of Search • Crawler – Discovers content – Least privilege permissions – Schedule versus continuous crawl (2013) • Indexing – Title & Description – Content – Meta Data
  5. 5. Mechanics of Search • Ranking – Relevancy ranking – Popular items – “Likes” or Ratings – Best Bets • Results – Refiners – Crawled and Managed properties – Document preview – Content Search web parts
  6. 6. Basic Search Principals
  7. 7. Basic Search Principals • Make sure search is configured & working • Meta data, meta data, meta data • Enable content ratings or “likes” • Review search logs • Manage content sources • Monitor search activity • Understand search structure
  8. 8. Unmanageable Search Results
  9. 9. Meta data • Information automatically extracted from content – Title – Description – Author – Date – Contents • Additional properties captured on content – Content Types – Site Columns
  10. 10. Content Rankings • General purpose ranking models. – General purpose ranking for most types of search results. • People search ranking models. – Calculate how relevant search results are based on social distance and expertise. • Special purpose ranking models. – Special purpose ranking model to calculate the ranking score for recommendations such as popularity, recommender based upon related items
  11. 11. How do items rank? Content These are the words contained in the items. For items that are text based, such as documents, this is typically most of the text. For other types of items, such as videos, there is little or no content. Metadata The metadata associated with items such as title, author, URL and creation date. Metadata is automatically extracted from most types of items. Web graph data This is information such as authority (from authoritative pages settings) and anchor text (from the hyperlinks associated with the item, and items linking to the item). File type Some file types can be considered more important for ranking than others. For example, Word and PowerPoint results are typically more important than Excel results. Interaction Information about the number of times a search result is clicked, and which queries led to a result being clicked.
  12. 12. Advanced Search Principals
  13. 13. Advanced Search Principals • Pay attention to site structure & navigation • Understand the content being published • Understand how people find information • Content types and Meta data – Global content types – Leverage Managed Metadata & Term sets • Search schema – Crawled Properties – Managed properties – Query Rules
  14. 14. Manageable Search Results
  15. 15. META DATA
  16. 16. Plan Content Types • Base set of required columns – Department – Document Type • Use Managed Metadata Term sets • Configured on all document libraries • Create custom library templates
  17. 17. Search Schema • Crawled Properties – The contents and metadata of the items that you crawl – Author, File Type • Managed Properties – Map crawled properties to managed properties – Default properties – Custom Properties
  18. 18. Query Rules • Best bets & keywords (2010) • Result blocks • Changing the query – Ranking changes based upon: • Keyword match • URL matching • Content Types • Tags • File types • Custom ranking models
  19. 19. Why care?
  20. 20. Search Focused Sites
  21. 21. Search Focused Sites • Heavy use of meta data and tagging • Dynamic presentation of information • Focused on the end user experience
  22. 22. Search driven content
  23. 23. Popular or Recent Items
  24. 24. Dynamic Mashups
  25. 25. Custom branding
  26. 26. Custom branding
  27. 27. Document management
  28. 28. Offices directory
  29. 29. O365 & Delve
  30. 30. O365 & Delve
  31. 31. Search Topologies
  32. 32. Structuring for Effective Search • Search Service Application Topology Small Farm Search Optimized Farm
  33. 33. Detroit 1500 Woodward Ave Suite 400 Detroit, MI 48226 (248) 546-1800 Thank You Grand Rapids 15 Ionia Ave SW Suite 270 Grand Rapids, MI 49503 (616) 776-1600 www.cdh.com

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