1 Email Viz Future Directions Marti Hearst UC Berkeley.

1

Email VizFuture Directions

Marti HearstUC Berkeley

2

Outline

• Important Infoviz Principle• Tough Data Mining Problem

– The infrequent important thing

• Interfaces tailored to user goals– Intelligence Analysts– Investigative Reporters

• Promising Future Directions– Integration of task, viz, and content analysis– Mixed-Initiative Interaction

3

Important InfoViz Principle

Distinguish between:

PRESENTATION ANALYSIS

4

Tough Data Mining Problem

• It’s easy to see the main trends• But often we want the rare but

unexpected and important event:– Russian oil company example– Schwarzenegger and Enron– Cigarettes and kids– Person on the periphery who is

working stealthily to influence things• Deep throat

5

Intelligence Analysts

6

Intelligence Analysts

• Interviews wit active counter-terrorist analysts

• Great diversity in– Goals– Computing environments

• Biggest problems are social/systemic

• Many mundane IT problems as well

7

Mundane IT Problems

• System incompatibilities• Data reformatting• Data cleaning• Documenting sources• Archiving materials

8

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

9

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.

10

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

11

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

12

Investigative Reporter Example

• Looking for trends in online literature

• Create, support, refute hypotheses

13

Investigative Reporter Example

What are the current main topics?

What are the new popular terms? How do they track with the news?

Clustering

Corpus-level statistics, Co-occurrence statistics

Contrasting collection statistics

14

Investigative Reporter Example

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?

Named-entity recognitionCreating a list of termsApply the list to a Subcollection

Create regex rules withPOS information

15

Integration

• TAKMI, by Nasukawa and Nagano, IBM systems Journal 40(4), 2001

• The system integrates:– Real tasks (CRM, patent analysis)– Content analysis– Information Visualization

16

TAKMI, by Nasukawa and Nagano, 2001Docs containing “windows 98”

17

CRM

TAKMI, by Nasukawa and Nagano, 2001

18

TAKMI, by Nasukawa and Nagano, 2001

19

TAKMI, by Nasukawa and Nagano, 2001

20

TAKMI, by Nasukawa and Nagano, 2001

21

TAKMI, by Nasukawa and Nagano, 2001

22

TAKMI, by Nasukawa and Nagano, 2001

23

Mixed-Initiative Interaction

• Balance control between user and agent– In Spotfire demo, system adjusts axes after

“other” category hidden– EDA:

• User selects a subset of data based on interesting-looking grouping

• System then does stats on this subset in the background while user continues to work

• Then system notifies user of interesting trends• See the AIDE system:

– St. Amant, R., Dinardo, M. D., and Buckner, N. (2003). Balancing Efficiency and Interpretability in an Interactive Statistical Assistant. Proceedings of IUI.