1. Simultaneous Support for Finding and Re-Finding
Jaime Teevan
Microsoft Research

2. People to re-find
Cockburn et al found 80% of Web page visits were re-visits
Teevan et al found 40% of searches lead to repeat dicks

3. New results become available
Selberg & Etzioni 2000 found results change a lot

4. Log analysis that shows people click on old and new results when returning to result pages. (27% of repeat searches click on new results!)

5. How to help people re-find
1. Relevance feedback – promote results lively to be re-found
A la Teevan et al work on personalization
BUT Teevan et al found change hurts
26% of time repeat searches at different rank.
94 seconds to re-click v. 192 seconds to re-click.
Similar to work with dynamic menus by Mitchell and Shneiderman 1989
2. Cache results
A la Rekimoto 1999 and Hayashi et al. 1998
Problem: No access to new info, and Teevan et al show people click new and old results for repeat searches

6. “Pick a card, any card.”

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

8. Your Card is GONE!

9. People Forget a Lot

10. Change Blindness

11. Change Blindness Other HCI research using charge blindness:
E.g., Durlash Help people notice charge
My research wants to take advantage of people’s failure to notice charge
Some graphics systems do this for rendering

13. We still need magic!

14. Re:Search Engine Architecture
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

15. 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

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

17. 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
O(mn) – O(n^3) – but can be implemented faster
In practice, basically linear with m 10 t
b10 s 10 … m1 … 7 m2 …
Slots
m10
Old

18. Re:Search Engine Architecture
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

19. 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

20. 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?”)

21. Intelligent Merging Supports Re-Finding and New-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

22. Summary People re-find often Solution: Re:Search Engine
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

23. Future Work Improve and generalize model Effectively use 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?

24. Jaime Teevan teevan@microsoft.com Microsoft Research