1. Interfaces for Intense Information Analysis
Marti Hearst
UC Berkeley
This research funded by ARDA

2. Outline A contrast Goals for three user groups
Search vs. Analysis
Goals for three user groups
Intelligence Analysts
Biomedical Researchers
Investigative Reporters
Our current interface design

3. Finding hay in a haystack
Search vs. Analysis
Search:
Finding hay in a haystack
Analysis:
Creating new hay

4. UIs for Search vs. Analysis
A necessary but undesirable step in a larger task
UI should not draw attention to itself
UI should be very easy to use for everyone
Analysis:
The larger task
UI can be more of a “science project”
But UI should have “flow”

5. General Goals Support hypothesis formation / refutation Flow
Easy creation, destruction, and cataloging of connections and coverage
Easy movement between multiple views
Represent:
Multiple supporting clues
Conflicting evidence
Uncertainty
Timeliness
Non-monotonicity

6. Intelligence Analysts

7. Intelligence Analysts
I have recently interviewed several active counter-terrorist analysts
Great diversity in
Goals
Computing environments
Biggest problems are social/systemic
Many mundane IT problems as well

8. Mundane IT Problems System incompatibilities Data reformatting
Data cleaning
Documenting sources
Archiving materials

9. Intelligence Analysts: Problem 1
Look at a series of reports, images, communication patterns;
Try to build a model of what is going on
Follow leads
Compare to previous situations
Recent problem:
Groups are changing their behavior patterns quickly
Very little use of sophisticated software tools

10. Intelligence Analysts: Problem 2
Given a large collection
“Roll around” in the data
See what has been “touched”
Tools should indicate which parts of the collection have been examined and which have yet to be looked at, and by whom
View data in several different ways
Data reduction methods such as MDS, SVD, and clustering often hide important trends.

11. Intelligence Analysts: Problem 2
Don’t show the obvious
e.g., Cheney is president
Don’t show what you’ve already shown
Only show the most recent version
Show which info is not present
Changes in the usual pattern
Something stops happening

12. Intelligence Analysts: Problem 3
Prepare a very short executive summary for the purposes of policy making
Really the culmination of a cascade of summaries
Reps from different agencies meet and “pow-wow” to form a view of the situation
Rarely, but crucially, must be able to refer back to original sources and reasoning process for purposes of accountability

13. BioInformatics Researchers

14. BioInformatics Example 1
How to discover new information …
… As opposed to discovering which statistical patterns characterize occurrence of known information.
Method:
Use large text collections to gather evidence to support (or refute) hypotheses
Make Connections
Gather Evidence

15. Etiology Example Don Swanson example, 1991 Goal: find cause of disease
Magnesium-migraine connection
Given
medical titles and abstracts
a problem (incurable rare disease)
some medical expertise
find causal links among titles
symptoms
drugs
results

16. Gathering Evidence stress CCB migraine magnesium magnesium PA SCD

17. Gathering Evidence
stress
CCB PA
SCD
migraine
magnesium

18. Swanson’s Linking Approach
Two of his hypotheses have received some experimental verification.
His technique
Only partially automated
Required medical expertise

19. BioInformatics Example 2:
How to find functions of genes?
Have the genetic sequence
Don’t know what it does
But …
Know which genes it coexpresses with
Some of these have known function
So …infer function based on function of co-expressed genes
This is problem suggested by Michael Walker and others at Incyte Pharmaceuticals

20. Gene Co-expression: Role in the genetic pathway
Kall.
Kall. g? h?
PSA
PSA
PAP
PAP g?
Other possibilities as well

21. Make use of the literature
Look up what is known about the other genes.
Different articles in different collections
Look for commonalities
Similar topics indicated by Subject Descriptors
Similar words in titles and abstracts
adenocarcinoma, neoplasm, prostate, prostatic neoplasms, tumor markers, antibodies ...

23. Formulate a Hypothesis
Hypothesis: mystery gene has to do with regulation of expression of genes leading to prostate cancer
New tack: do some lab tests
See if mystery gene is similar in molecular structure to the others
If so, it might do some of the same things they do

24. Investigative Reporter Example
Looking for trends in online literature
Create, support, refute hypotheses

25. Investigative Reporter Example
Clustering
Corpus-level statistics,
Co-occurrence statistics
Contrasting collection
statistics
What are the current main topics?
What are the new popular terms?
How do they track with the news?

26. Investigative Reporter Example
Named-entity recognition
Creating a list of terms
Apply the list to a
Subcollection
Create regex rules with
POS information
How long after a new Star Trek series comes on the air before characters from the series appear in stories?
How often do Klingons initiate attacks against Vulcans, vs. the converse?

27. LINDI Summary Term Set Query Analysis Document Set File Help
New
Merge
All terms: *
a c
u y
m z
Diseases: emphysema cancer hypertension …
Query x x
Analysis
Document Set
All documents: *
WHO: organization = world health organization

28. Thank you!
For more information:
bailando.sims.berkeley.edu/lindi.html