Download - 1 Interfaces for Intense Information Analysis Marti Hearst UC Berkeley This research funded by ARDA
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Outline
• A contrast– Search vs. Analysis
• Goals for three user groups– Intelligence Analysts– Biomedical Researchers– Investigative Reporters
• Our current interface design
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UIs for Search vs. Analysis
• Search: – 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”
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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
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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
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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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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
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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
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Swanson’s Linking Approach
• Two of his hypotheses have received some experimental verification.
• His technique– Only partially automated– Required medical expertise
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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
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Gene Co-expression:Role in the genetic pathway
g?
PSA
Kall.
PAP
h?
PSA
Kall.
PAP
g?
Other possibilities as well
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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 ...
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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
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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
LINDI File Help
Summary
Query
Analysis
Term Set
Document Set
a c u y m z
x x
All terms: *
All documents: *
New
Merge
Diseases: emphysema cancer hypertension …
WHO: organization = world health organization