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Email VizFuture Directions

Marti HearstUC Berkeley

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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

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Important InfoViz Principle

Distinguish between:

PRESENTATION ANALYSIS

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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

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Intelligence Analysts

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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

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Mundane IT Problems

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

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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

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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.

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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

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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

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Investigative Reporter Example

• Looking for trends in online literature

• Create, support, refute hypotheses

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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

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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

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Integration

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

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

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

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CRM

TAKMI, by Nasukawa and Nagano, 2001

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TAKMI, by Nasukawa and Nagano, 2001

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TAKMI, by Nasukawa and Nagano, 2001

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TAKMI, by Nasukawa and Nagano, 2001

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TAKMI, by Nasukawa and Nagano, 2001

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TAKMI, by Nasukawa and Nagano, 2001

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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.