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Simultaneous Support for Finding and Re-Finding

This research explores the Re:Search Engine architecture and its merge algorithm, which supports both re-finding and new-finding. Studies show that the Re:Search Engine effectively utilizes memory lapses to the user's advantage, improving search results. Future work involves improving and generalizing the model and effectively highlighting and presenting changes at the right time.

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Simultaneous Support for Finding and Re-Finding

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  1. Simultaneous Support for Finding and Re-Finding Jaime Teevan teevan@microsoft.com Microsoft Research

  2. “Pick a card, any card.”

  3. Abracadabra! Case 1Case 2Case 3Case 4Case 5Case 6

  4. Your Card is GONE!

  5. People Forget a Lot

  6. Change Blindness

  7. Change Blindness

  8. We still need magic!

  9. Re:Search Engine Architecture Search engine result list query 1 query 2 … query n result list 1 result list 2 … result list n Index of past queries score 1 score 2 … score n Result cache Merge query result list User interaction cache Web browser User client

  10. Components of Re:Search Engine query 1 query 2 … query n query Index of past queries score 1 score 2 … score n • Index of Past Queries • Result Cache • User Interaction Cache • Merge Algorithm result list 1 result list 2 … result list n query 1 query 2 … query n Result cache User interaction cache result list result list 1 result list 2 … result list n Merge result list

  11. Merge Algorithm result list result list 1 result list 2 … result list n Merge result list m1 m2 b1 b2 b3

  12. Choosing the Best Possible List • Consider every combination • Include at least three old and three new • Min-cost network flow problem New b1 … b2 7 10 t b10 s 10 … m1 … 7 m2 … Slots m10 Old

  13. Re:Search Engine Architecture Search engine result list query 1 query 2 … query n result list 1 result list 2 … result list n Index of past queries score 1 score 2 … score n Result cache Merge query result list User interaction cache Web browser User client

  14. Merged List Appears The Same • 132 participants – between subjects • Merge types • Intelligent Merge • Original • New • Dumb Merge • Intelligent Merge like the Original list • Dumb Merge and New looked different • Intelligent Merge • Original • New • Dumb Merge

  15. Study of How Lists Are Used • 42 participants – within subjects • Two sessions a day apart • 12 tasks each session • Tasks based on queries • Queries selected based on log analysis • Session 1 • Session 2 • Re-finding • New-finding (“stomach flu”) (“Symptoms of stomach flu?”) (“Symptoms of stomach flu?”) (“What to expect at the ER?”)

  16. Intelligent Merging Supports Re-Finding and New-Finding • Re-finding • Intelligent merging better than dumb merging • Almost as good as using the original list • New-finding • No difference between new list and intelligent • Intelligent merging best of both worlds

  17. Summary • People re-find often • Support re-finding • By supporting consistency • Allow new-finding • Solution: Re:Search Engine • Uses memory lapses to user’s advantage • Architecture (focus: merge algorithm) • Studies show Re:Search Engine works

  18. Future Work • Improve and generalize model • More sophisticated measures of memorability • Other types of lists (inboxes, directory listings) • Effectively use model • Highlight change as well as hide it • Present change at the right time • This talk’s focus: how • What about when to display new information?

  19. Jaime Teevan teevan@microsoft.com Microsoft Research

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