2003.04.10chi 2003 – visualization & navigation1 efficient user interest estimation in fisheye...
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2003.04.10 CHI 2003 – Visualization & Navigation 1
Efficient User Interest Efficient User Interest Estimation in Fisheye ViewsEstimation in Fisheye Views
Jeffrey Heer and Stuart K. Card1 Palo Alto Research Center, Inc.2 University of California, Berkeley
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RoadmapRoadmap
Motivation + Background Implementation Evaluation Conclusion
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Degree of Interest (DOI)Degree of Interest (DOI)
Models user’s spontaneous interest across the tree– This model can then be used to inform presentation
-3 -3 -3 -3 0 -1 -2 -2
-2 -2 0 -1
-1
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Computed Degree of Interest
0 -1
0 -1
-1
0
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Cull low Degree of Interest
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User Modeling in Fisheye ViewsUser Modeling in Fisheye Views
6 6 6 6 0 2 4 4
5 5 1 3
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Degree of Interest Intrinsic Importance + Distance from Point of Interest
3 3 3 3 3 3 3 3
2 2 2 2
1
0
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Intrinsic Importance Distance from Point of Interest
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… … the need for speedthe need for speed
Visualization should respond fluidly to user actions
But for each interaction, may have to– Recompute DOI– Recompute Layout
Hard time limit: 100ms (Card, Moran, Newell) Goal:
– Limit all computations to the number of displayed nodes.
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Naïve Interest ComputationNaïve Interest Computation
-3 -3 -3 -3 0 -1 -2 -2
-2 -2 0 -1
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Requires visiting the entire tree!
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Least Common Ancestor PruningLeast Common Ancestor Pruning
-3 -3 -3 0 -1 -2 -2
-2 -2 0 -1
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-2 -2 0 -1
-1 0
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-3-3
Limit computation to the subtree rooted at least common ancestor.
However, no savings if new focus is here
Furthermore, this method exploits a specific DOI distribution not necessarily generalizable
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Solution: Disinterest ThresholdingSolution: Disinterest Thresholding
Saturate DOI function at a disinterest threshold– Compute DOI only for visible nodes– Use thresholding to supply defaults for the others
-2 -2 -2 -2 0 -1 -2 -2
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Computed DOI: minDOI = -1
0 -1
0 -1
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Cull low Degree of Interest
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Disinterest ThresholdingDisinterest Thresholding
-2 -2 -2 -2 0 -1 -2 -2
-2 -2 0 -1
-1
0
0
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Node Attribute RegistryNode Attribute Registry
Backing array data structure: table of node attributes.
Tag visible nodes with table index. When attributes are needed (e.g. node.getX()), the table is consulted. – If the node is in the table, the attribute is simply returned.– Else, the suitable default is supplied
» DOI: minimum DOI, Position: position of first visible ancestor
index dirty DOI x y size color etc…
0 1 0 213 12 5 … …..
1 1 -1 134 58 4 … …..
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EvaluationEvaluation
0.000
0.020
0.040
0.060
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1 10 100 1000 10000 100000 1000000
Number of Nodes
DO
I Cal
cula
tio
n T
ime
(sec
)
naïve
least common ancestor
disinterest
Setup:
Time walks through algorithmically generated DOITrees with increasing tree depths.
Test System:
PIII 1GHz, 256MB RAM 16 MB Video RAM DOI Threshold = -2
Naïve and LCA grow linearly with the number of nodes.
Disinterest thresholding grows linearly with number of visible nodes, which in this case grows logarithmically with total number of nodes.
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LimitationsLimitations
Doesn’t improve cases where there are a large number (10,000+) visible nodes.
Smooth interaction also dependent on the use of efficient layout algorithms.
Only approximates DOI distribution, which may be problematic if applications wish to use DOI for more than visualization.
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Thanks!!Thanks!! Questions? Questions?
Jeffrey Heer [email protected]
Stuart K. Card [email protected]
0 -1 -2 -2
0 -1
0
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MotivationMotivation
The real design problem is not increased access to information, but greater efficiency in finding useful information.
Increasing the rate at which people can find and use relevant information improves human intelligence.
Amount ofAccessibleKnowledge
Amount ofAmount ofAccessibleAccessibleKnowledgeKnowledge
Cost [Time]Cost [Time]Cost [Time]
Amount ofAccessibleKnowledge
Amount ofAmount ofAccessibleAccessibleKnowledgeKnowledge
Cost [Time]Cost [Time]Cost [Time]
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Information VisualizationInformation Visualization
1.2 b/s (Reading)2.3 b/s (Pictures)
Leverage highly-developed human visual system to achieve rapid understanding of abstract information.
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Node Attribute RegistryNode Attribute Registry
DOI function only sets DOI for nodes above the disinterest threshold.– Nodes are transparently added to registry when DOI is set.– If node is already there, then dirty bit is set.– Registry is resized as necessary.
After DOI computation, non-dirty nodes are removed from registry, dirty bits are cleared.
Result: DOI computation time proportional to the number of nodes displayed!