the perfect search engine is not enough
Download
Skip this Video
Download Presentation
The Perfect Search Engine Is Not Enough

Loading in 2 Seconds...

play fullscreen
1 / 31

The Perfect Search Engine Is Not Enough - PowerPoint PPT Presentation


  • 89 Views
  • Uploaded on

The Perfect Search Engine Is Not Enough. Jaime Teevan † , Christine Alvarado † , Mark S. Ackerman ‡ and David R. Karger †. † MIT, CSAIL ‡ University of Michigan. Let Me Interview You!. Email:. What’s the last email you read? What did you do with it?

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'The Perfect Search Engine Is Not Enough' - lilianna


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
the perfect search engine is not enough

The Perfect Search Engine Is Not Enough

Jaime Teevan†, Christine Alvarado†, Mark S. Ackerman‡ and David R. Karger†

† MIT, CSAIL

‡ University of Michigan

let me interview you
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:
  • What’s the last Web page you visited? How did you get there?
  • Have you looked for anything on the Web?
  • Files:
  • What’s the last file you looked at? How did you get to it?
  • Have you looked for a file?
overview understanding
Overview:Understanding

Search

Directed

  • Introduction
  • Related work
  • Methodology
  • What we learned
    • How?
    • Why?
    • Who?
    • So what?
  • Introduction
  • Related work
  • Methodology
  • What we learned
    • How?
    • Why?
    • Who?
    • So what?
haystack personal information storage

Haystack

Haystack:Personal Information Storage

Web pages

Email

Files

Calendar

Contacts

directed search in haystack
Directed Search in Haystack

What was that paper I read last week about Information Retrieval?

Haystack

directed search in haystack6
Directed Search in Haystack

Ah yes!

Thank you.

Haystack

“Perfect Search Engine”

related work
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
modified diary study
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
overview understanding9
Overview:Understanding

Directed

Search

  • Introduction
  • Related work
  • Methodology
  • What we learned
    • How?
    • Why?
    • Who?
    • So what?
directed search today
Directed Search Today
  • Target: Connie Monroe’s office number

 Type into a search engine:

“Connie Monroe, office number”

what we observed
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

what we observed12
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.

what we observed13
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.”

strategies looking for information
Strategies Looking for Information

Teleporting

Orienteering

why do people orienteer
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
easier than saying what you want
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
you know where you are
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
you know what you find
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…”

individual search behavior
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
how individuals search for files
How Individuals Search For Files

Filers

Big steps

Pilers

Small steps

more to learn from the data
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

applying what we learned
Applying What We Learned

 Support orienteering

  • 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
more to learn from the data23
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

structural consistency important
Structural Consistency Important

All must be the same to re-find the information!

preserve what user remembers
Preserve What User Remembers
  • Supports orienteering for re-finding
  • Allows access to new information
searching other collections
Searching Other Collections

Ah yes!

Thank you.

keep population in mind
Keep Population in Mind
  • CS grad students not representative
  • Very familiar with search tools

 Would expect to see lots of tool use

relating how and what
Relating How and What
  • People only keyword search 39% of the time
  • What people look for related to how they look

Orienteer to specific information

  • Surprise:
relating how and corpus
Relating How and Corpus
  • Email and files: Almost never keyword searched
  • Easy to associate information with document
  • Web: Used keyword search much more often
relating what and corpus
Relating What and Corpus
  • Email searches were primarily for specific information
  • File searches were primarily for documents
  • Web searches were more evenly distributed
ad