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1 / 17 Visualization of GTD and Multimedia Remco Chang Charlotte Visualization Center UNC Charlotte

1 / 17 Visualization of GTD and Multimedia Remco Chang Charlotte Visualization Center UNC Charlotte

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Visualization of GTD and Multimedia

Remco ChangCharlotte Visualization Center

UNC Charlotte

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Visual GTD Flow Chart

Entity Relationships(Geo-temporal Vis)

Dimensional Relationships(ParallelSets)

Entity Analysis(Search By Example)

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Five Flexible Entry Components

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Seeing Patterns…

FARC showing an outlier Unusual temporal

pattern of NPA

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Parallel Sets View

• Parallel Sets– Displays

relationships among categorical dimensions

– Shows intersections and distributions of categories

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Parallel Sets View

• Dynamic filtering on continuous dimensions can show more information

• Here we see the large proportion of facility attacks and bombings in Latin America during the early 1980s

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ParallelSets - Framing

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Entity Comparison

• Uses the algorithm “Longest Common Subsequence” (LCS) to identify similar patterns

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Grouping using MDS in 2D

• Each o represents a terrorist group

• Groups form cluster according to naturally occurring trend sizes

• Clusters are easily visible

MDS Analysis by Country

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Auto Video Extraction

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Multimedia Visual Analysis

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Concept Graph

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Video Analysis Example

CNN Fox News MSNBC• News contains view points and opinions• Find local, regional, national, and international reports of the

same event to get a complete picture

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News Lens

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Integrating Terrorism Data Analysisand News Analysis

Terrorism Databases

Terrorism Visual

Analysis

News Story Databases

News Visual

Analysis

Jigsaw

TerrorismVA

BroadcastVA

Stab/TIBORReasoningEnvironment

Framing,Affective Analysis

NVAC

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Future Work

• Event-based video analysis

• Smart Visual GTD– Collaboration with Daniel Kiem (Univ Konstanz,

Germany)– Multimedia Analysis

• Collaboration with PNNL (A. Sanfilipo, W. Pike)• Analyzes (layout of) webpages, videos, images, and

unstructured texts.• Tracking temporal changes

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Questions?

Thank you!

[email protected]://viscenter.uncc.edu

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Backup

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Entity Comparison• Two strings of data (each representing a series of events)

– GATCCAGT– GTACACTGAG

• Basic algorithm returns length of longest common subsequence: 6

• Can return trace of subsequence if desired:–GTCCAG

• GATCCAGT• GTACACTGAG

• Additional variations can take into account event gap penalties, time gap penalties, and exploration of shorter, or alternate, common subsequences

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ParallelSets - Framing