Constellation: A Visualization Tool for Linguistic Queries from MindNet

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Constellation A Visualization Tool for
Linguistic Queries from MindNet

• Tamara Munzner
• François Guimbretière
• Stanford University
• George Robertson
• Microsoft Research

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Overview

• solve specific problem
• help linguists improve MindNet algorithms
• chosen techniques
• custom semantic layout
• perceptual channels
• interaction as first-class citizen

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Definition Graph

• dictionary entry sentence
• nodes word senses
• links relation types

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Semantic Network

• definition graphs as building blocks
• unify shared words
• large network
• millions of nodes
• global structure known dense
• probes return local info
• uses
• grammar checking, automatic translation

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Path Query

• best N paths between two words
• words on path itself

• definition graphs used in computation

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Task Plausibility Checking

• paths ordered by computed plausibility
• researcher hand-checks results
• high-ranking paths believable?
• believable paths high-ranked?
• gross polluters (stop words)

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Top 10 Paths kangaroo - tail
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Top 10 Paths kangaroo - tail
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Goal

• create unified view of relationships between
  paths and definition graphs
• shared words are key
• thousands of words (not millions)
• special-purpose algorithm debugging tool
• not understand the structure of English

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Semantic Layout

• reflect dataset characteristics
• path ordering as backbone
• fill in definition graphs

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Semantic Layout

• plausibility gradient

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Semantic Layout

• plausibility gradient
• horizontal position

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Semantic Layout

• plausibility gradient
• horizontal position
• size

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Semantic Layout

• edge crossings not minimized

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Semantic Layout

• edge crossings not minimized
• false attachment solved with interactive
  selective emphasis

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Perceptual Channels

• redundant combinations
• synergy from multiple codings
• layout gradient
• spatial position, word size
• quantitative

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Perceptual Channels

• highlightingvisual popout
• saturation
• brightness
• linewidth
• ordered
• although binary

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Perceptual Channels

• highlightingvisual popout
• saturation
• brightness
• linewidth
• ordered
• although binary

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Perceptual Channels

• hue
• relation types
• green part-of
• red is-a
• cyan modifier
• word types
• yellow path
• green definition graph
• blue leaf
• selective (nominal)

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Perceptual Channels

• orientation
• relation types
• axis-aligned local
• slanted long distance
• between instancesof same word
• selective (nominal)

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Perceptual Channels

• enclosure
• definition graphs associated with path word
• hierarchy

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Interaction

• see video

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Video

• zoom
• software vs. video

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Semantic Layout Challenges

• spatial position encodes path ordering
• edge crossings not minimized
• clutter reductioninteraction, perceptual
  channels
• tradeoffs
• spatial encoding vs. information density
• navigation intelligent zooming
• global, intermediate, local

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Semantic Layout Challenges

• navigation
• intelligent zooming
• global
• path structure overview
• intermediate
• association of path word and definition graphs
• local
• read single definition graph

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Color Scheme Reynolds94

• hues
• maximally separated on color wheel
• saturation/brightness
• low for unobtrusive, high for emphasis
• maximal CRT legibility
• black text on colored background

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Conclusion

• targeted case study
• small user community
• techniques
• encode dataset structure spatially
• multiple perceptual channels
• interactive selective emphasis, navigation
• approach broadly applicable

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Acknowledgements

• MSR linguists
• Lucy Vanderwende, Bill Dolan, Mo Corston-Oliver
• iterative design techniques
• Mary Czerwinski
• discussion
• Maneesh Agrawala, Pat Hanrahan, Chris Stolte,
  Terry Winograd
• funding
• Microsoft Graduate Research Fellowship, Interval
  Research
• http//graphics.stanford.edu/papers/const
• http//graphics.stanford.edu/munzner/talks/vis99

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