Constellation: A Visualization Tool for Linguistic Queries
from MindNet
Tamara Munzner
François GuimbretièreStanford University
George RobertsonMicrosoft Research
Overview
• solve specific problem– help linguists improve MindNet algorithms
• chosen techniques– custom semantic layout– perceptual channels– interaction as first-class citizen
Definition Graph• dictionary entry sentence• nodes: word senses• links: relation types
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
Path Query• best N paths between two words
• words on path itself
• definition graphs used in computation
Task: Plausibility Checking
• paths ordered by computed plausibility
• researcher hand-checks results– high-ranking paths believable?– believable paths high-ranked?– gross polluters (stop words)
Top 10 Paths: kangaroo - tail
Top 10 Paths: kangaroo - tail
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
Video
• zoom– software vs. video
Semantic Layout Challenges
• spatial position encodes path ordering– edge crossings not minimized– clutter reduction:
interaction, perceptual channels
• tradeoffs– spatial encoding vs. information density
• navigation: intelligent zooming– global, intermediate, local
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
Conclusion
• targeted case study – small user community
• techniques– encode dataset structure spatially– multiple perceptual channels– interactive selective emphasis, navigation
• approach broadly applicable
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