1. The Perfect Search Engine Is Not Enough Jaime Teevan †, Christine Alvarado †, Mark S. Ackerman ‡ and David R. Karger † † MIT, CSAIL ‡ University of Michigan

2. Let Me Interview You! Email: – What’s the last email you read? What did you do with it? – Have you gone back to an email you’ve read before? Web: Files: – What’s the last Web page you visited? How did you get there? – Have you looked for anything on the Web? – What’s the last file you looked at? How did you get to it? – Have you looked for a file?

3. Search Overview: Understanding Introduction Related work Methodology What we learned – How? – Why? – Who? – So what? Directed Introduction Related work Methodology What we learned – How? – Why? – Who? – So what?

4. Haystack: Personal Information Storage Email Web pages Files Calendar Contacts Haystack

5. Directed Search in Haystack What was that paper I read last week about Information Retrieval? Haystack

6. Directed Search in Haystack Ah yes! Thank you. Haystack “Perfect Search Engine”

7. Related Work Directed search – Lab studies [Capra03, Maglio97] – Log analysis [Broder02, Spink01] Observational studies [Malone83] Information Seeking – Marchionini, O’Day and Jeffries, Bates, Belkin, … – Evolving information need

8. Modified Diary Study Subjects: 15 CS graduate students Ten interviews each (2/day x 5 days) Two question types – Last email/file/Web page looked at – Last email/file/Web page looked for Supplemented with direct observation and an hour-long semi-structured interview

9. DirectedSearch Overview: Understanding Introduction Related work Methodology What we learned – How? – Why? – Who? – So what?

10. Directed Search Today Target: Connie Monroe’s office number  Type into a search engine: “Connie Monroe, office number”

11. What We Observed Interviewer: Have you looked for anything on the Web today? Jim: I had to look for the office number of the Harvard professor. I: So how did you go about doing that? J: I went to the homepage of the Math department at Harvard

12. What We Observed I: So you went to the Math department, and then what did you do over there? J: It had a place where you can find people and I went to that page and they had a dropdown list of visiting faculty, and so I went to that link and I looked for her name and there it was.

13. What We Observed J: I knew that she had a very small Web page saying, “I’m here at Harvard. Here’s my contact information.”

14. Strategies Looking for Information Teleporting Orienteering

15. Why Do People Orienteer? Easier than saying what you want You know where you are You know what you find The tools don’t work

16. Easier Than Saying What You Want Describing the target is hard – Can’t – Prefer not to Habit – “Whichever way I remember first.” Search for source – E.g., Your last email search

17. You Know Where You Are Stay in known space – URL manipulation – Bookmarks – History Backtracking – Following an information scent – Never end up at a dead end

18. You Know What You Find Context gives understanding of answer “I was looking for a specific file. But even when I saw its name, I wouldn’t have known that that was the file I wanted until I saw all of the other names in the same directory…” Understanding negative results “I basically clicked on every single button until I was convinced… I don’t think that it exists…”

19. Individual Search Behavior Search behavior varied by individual Categorize based on email usage – Filers – Pilers People who pile information take small steps People who file information take big steps

20. How Individuals Search For Files Filers Pilers Big steps Small steps

21. More to Learn from the Data Differences in finding v. re-finding How organization relates to search Importance of type (email, files and Web) Looked at v. looked for  Keep in mind population

22.  Support orienteering Applying What We Learned Advantages to orienteering – Easier than saying what you want – You know where you are – You know what you find Individual differences in step size – Highlight source (e.g., flag sources with info) – Integrate tools used for steps – Support exhaustive search – Allow for different step sizes

23. More to Learn from the Data Differences in finding v. re-finding How organization relates to search Importance of type (email, files and Web) Looked at v. looked for  Keep in mind population

24. Structural Consistency Important All must be the same to re-find the information!

25. Supports orienteering for re-finding Allows access to new information Preserve What User Remembers

26. File or Pile Email Filer Piler

27. Searching Other Collections Ah yes! Thank you.

28. Keep Population in Mind CS grad students not representative Very familiar with search tools  Would expect to see lots of tool use

29. Orienteer to specific information Relating How and What People only keyword search 39% of the time What people look for related to how they look SpecificGeneralDocument Other471941 Keyword342317 Surprise:

30. Relating How and Corpus Email and files: Almost never keyword searched Easy to associate information with document Web: Used keyword search much more often EmailFilesWeb Other594219 Keyword06061064

31. Relating What and Corpus EmailFilesWeb Specific39733 General10730 Document08083514 Email searches were primarily for specific information File searches were primarily for documents Web searches were more evenly distributed