Ticer - Search And Facets

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Ticer - Search And Facets

  1. 1. Summa/Search and Facets Digital Libraries à la Carte 2009 Tilburg University, 2009-07-31 Mads Villadsen <mv@statsbiblioteket.dk>
  2. 2. A Short History of Summa/Search
  3. 3. Why?  Improve response times  Greater flexibility to create a system that had end user concerns as a priority  Expose all our resources through a single point of entry  Combine IT knowledge with knowledge of library science
  4. 4. How Integrated search  Speed and meaningful ranking of material from different sources Exploratory search  Help users find what they are looking for – even if they don't quite know it themselves Motivational design  Show users the information they need when they need it
  5. 5. “Facets” – Limit Your Search Limit your search to certain material types
  6. 6. Facets – No Counts Proper facets. The facet counts came later.
  7. 7. Facets Today Proper facet counts. Only the most useful facets are shown.
  8. 8. Facet Information Current system at the State and University Library  9.1 million records  8.7 million unique tags in 15 facets  Average number of tags/document is 10  Large facets  Subject: 3.5 million unique tags  Author: 4.8 million unique tags
  9. 9. How Did It All Work Out?
  10. 10. Recent Usability Test: The Good  The Google-like initiatives  One simple search field  Search suggestions  Did-You-Mean  The integration of extra information in the full records – especially covers and abstracts  The Todo list
  11. 11. Recent Usability Test: What To Improve  Users had trouble finding journal articles  Many users failed to discover the facets  Further tweaking of the relevancy ranking  Simplification of the request procedure
  12. 12. What Now?
  13. 13. Simple Changes  Rename “order list” to “basket”  Make it possible to add any item to the Todo list  Move facets to the left side  ...
  14. 14. Search Tomorrow
  15. 15. More Data User expectations: If they can't find it in Search, then we don't have it. Particularly a problem with article level data. Will make the experience as a whole better for the end user.
  16. 16. Rethink Facet Presentation
  17. 17. Clustering Add clustering framework to facilitate automatic tag extraction. May link together articles, books, and data-sets that the user hadn't thought of. Should prove very useful with full text data.
  18. 18. Other  Rights integration  Duplicate reduction  User specific ranking  Further develop system and statistics tools  Index look-ups  And more...
  19. 19. Resources  The hybrid library: from the users perspective http://www.statsbiblioteket.dk/om-statsbiblioteket/brugbarhed/feltstudier  Summa Site http://statsbiblioteket.dk/summa/  Search Usability Test http://www.statsbiblioteket.dk/summa/search%20-%20usability-test-English.pdf  Code4lib 2009 presentation on Complete Faceting http://www.code4lib.org/conference/2009/eskildsen
  20. 20. Questions?

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