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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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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 highlighting: visual popout –saturation –brightness –linewidth ordered –although binary
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Perceptual Channels highlighting: visual 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 instances of 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 reduction: interaction, 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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