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