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© Anselm Spoerri Lecture 9 TheBrain & Visual Thesaurus Demos Focus+Context –Nonlinear Magnification –TableLens Visual Tools for Text Retrieval Part 1.

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Presentation on theme: "© Anselm Spoerri Lecture 9 TheBrain & Visual Thesaurus Demos Focus+Context –Nonlinear Magnification –TableLens Visual Tools for Text Retrieval Part 1."— Presentation transcript:

1 © Anselm Spoerri Lecture 9 TheBrain & Visual Thesaurus Demos Focus+Context –Nonlinear Magnification –TableLens Visual Tools for Text Retrieval Part 1

2 © Anselm Spoerri Hierarchical Information – Recap Treemap Traditional ConeTree

3 © Anselm Spoerri Hierarchical Information – The Brain Download Demo – http://www.thebrain.comhttp://www.thebrain.com Example Parent Siblings Children Lateral Links

4 © Anselm Spoerri Radial Layout Animation Animated Exploration of Dynamic Graphs with Radial Layout Shift of Focus −Straight-line path shift  produces confusing animation −“Linear interpolation of polar coordinates”  produces smooth transition (slow in and slow-out timing) Download VideoDownload Video (… will take a while) or http://www.scils.rutgers.edu/~aspoerri/Teaching/InfoVisResources/videos/ http://www.scils.rutgers.edu/~aspoerri/Teaching/InfoVisResources/videos/ and right click on “viz.avi” and save

5 © Anselm Spoerri Visual Thesaurus by Plumb Design http://www.visualthesaurus.com/ Displaying interrelationships between words and meanings Visual Thesaurus accesses data from WordNetWordNet –Publicly available lexical reference system developed by the Cognitive Science Laboratory at Princeton University –Contains over 50,000 words and 40,000 phrases collected into more than 70,000 sense meanings.

6 © Anselm Spoerri Visual Thesaurus

7 © Anselm Spoerri Focus+Context Interaction Nonlinear Magnification InfoCenter –http://www.cs.indiana.edu/~tkeahey/research/nlm/nlm.htmlhttp://www.cs.indiana.edu/~tkeahey/research/nlm/nlm.html Nonlinear Magnification = “Fisheye Views" = “Focus+Context" Preserve Overview enable Detail Analysis in same view

8 © Anselm Spoerri Focus+Context – Constrained Transformations

9 © Anselm Spoerri Focus+Context – DC Subway Map

10 © Anselm Spoerri Fisheye Menus B. Bederson –HCI Lab, Uni. of Maryland Demo http://www.cs.umd.edu/hcil/fisheyemenu/fisheyemenu-demo.shtml

11 © Anselm Spoerri Table Lens Download VideoDownload Video (… will take a while) or http://www.scils.rutgers.edu/~aspoerri/Teaching/InfoVisResources/videos/ http://www.scils.rutgers.edu/~aspoerri/Teaching/InfoVisResources/videos/ and right click on “tableLens.wmv” and save

12 © Anselm Spoerri Table Lens – Focus+Context hiddenfocal Non focal sorting spotlighting Control point

13 © Anselm Spoerri Table Lens (cont.) SHAPE –Pattern detection and comparison OUTLIERS –Detect extreme values –Sort to see MAX and MIN

14 © Anselm Spoerri Table Lens PositionYes SizeYes Orientation Texture Shape ColorYes Shading Depth Cues Surface MotionYes Stereo ProximityYes SimilarityYes ContinuityYes Connectedness Closure Containment Yes Direct ManipulationYes Immediate FeedbackYes Linked DisplaysYes Logarithmic Shift of Focus Dynamic Sliders Semantic ZoomYes Focus+ContextYes Details-on-Demand Output  Input Perceptual Coding Interaction Data = Multi– Variate

15 © Anselm Spoerri Table Lens Demo Table Lens http://www.inxight.com/products/sdks/tl/ Tasks – Ameritrade Table Lens Task 1 Find Shape for “5years” Column Find Min & Max for “Quarter to” Column Find Shape for “1year” Column Find Min & Max for “10years” Column Task 2 The Largest loss value for a fund for this Quarter Hint: greater than -30.0 The Largest ten year gain. Hint: greater than +900.0 The Largest five year gain. Hint: a Lipper fund See what else you can find...

16 © Anselm Spoerri Hyperbolic Trees Visualize Hierarchical Data Focus + Context Technique Inxigth StarTree Browser –http://www.inxight.com/products/sdks/st/http://www.inxight.com/products/sdks/st/ Approach –First lay out hierarchy on hyperbolic plane and map this plane to a disk –Root at center, subordinates around Apply recursively, distance decreases between parent and child as you move farther from center, children go in wedge rather than circle –Use animation to navigate along this representation of the plane Comparison –Standard 2D browser: 100 nodes (w/3 character text strings) –Hyperbolic browser: 1000 nodes, about 50 nearest the focus can show from 3 to dozens of characters Download VideoDownload Video (… will take a while) or http://www.scils.rutgers.edu/~aspoerri/Teaching/InfoVisResources/videos/ http://www.scils.rutgers.edu/~aspoerri/Teaching/InfoVisResources/videos/ and right click on “hyperbolicTree.mpeg” and save

17 © Anselm Spoerri Hyperbolic Trees PositionYes SizeYes Orientation Texture ShapeYes ColorYes Shading Depth Cues Surface MotionYes Stereo ProximityYes Similarity Continuity ConnectednessYes Closure Containment Direct ManipulationYes Immediate FeedbackYes Linked DisplaysYes Logarithmic Shift of FocusYes Dynamic Sliders Semantic ZoomYes Focus+ContextYes Details-on-DemandYes Output  Input Perceptual Coding Interaction Data = Hierarchy

18 © Anselm Spoerri Hyperbolic Tree  3D Munzner’s H3 / H3 Viewer http://graphics.stanford.edu/videos/h3/ http://graphics.stanford.edu/videos/h3/ Hyperbolic Browser Projection onto sphere rather than circle Handles graphs as well as trees ConeTree Distributes child nodes on surface of hemisphere rather than circle circumference

19 © Anselm Spoerri 3D Hyperbolic Browser  Walrus Developed Young Hyun at CAIDA, based on research by Tamara Munzner. http://www.caida.org/tools/visualization/walrus/

20 © Anselm Spoerri 3D Hyperbolic Browser  Walrus

21 © Anselm Spoerri Interaction Benefits Direct ManipulationReduce Short-term Memory Load Immediate Feedback Permit Easy Reversal of Actions Linked DisplaysIncrease Info Density Animated Shift of Focus Offload work from cognitive to perceptual system Object Constancy and Increase Info Density Dynamic SlidersReduce Errors Semantic Zoom  O(LOG(N)) Navigation Diameter Focus+Context  O(LOG(N)) Navigation Diameter Details-on-DemandReduce Clutter & Overload Output  InputReduce Errors

22 © Anselm Spoerri Interface Metaphors (as suggested by Mann) book bookshelf newspaper city landscape rooms building tower plus elevator guided tour lens butterfly pile galaxy starfield universe magnet sculpture television wall aquarium water flowing

23 © Anselm Spoerri Interface Metaphors

24 © Anselm Spoerri Interface Metaphors

25 © Anselm Spoerri Interface Metaphors

26 © Anselm Spoerri Interface Metaphors

27 © Anselm Spoerri How to Use Visualization to Support Retrieval Source Thomas Mann (PhD Thesis Uni of Konstanz) Visualization of search results from the World Wide Web http://www.ub.uni-konstanz.de/v13/volltexte/2002/751//pdf/Dissertation_Thomas.M.Mann_2002.V.1.07.pdf

28 © Anselm Spoerri Query Formulation – Boolean  FilterFlow OR AND Coordination Problem: which operator to choose? Most people find the basic Boolean syntax counter-intuitive. AND “implies” broadening (opposite true). OR “implies” narrowing (opposite true).

29 © Anselm Spoerri Query Formulation – Boolean  FilterFlow ( A or B or C) and (D or E) and (not F)  express common queries How?  Visualize “ Power Set ” Difficult to express complex queries

30 © Anselm Spoerri Query Formulation – Venn Diagrams  TeSS

31 © Anselm Spoerri Query Formulation – Venn Diagrams  VQuery 1. “AND” “OR” “NOT”  low visual saliency 2. How to generalize to higher number of sets?

32 © Anselm Spoerri Generalize Venn Diagrams

33 © Anselm Spoerri Goal – Compare Search Results TransformExplode Can be Generalized to N Sets

34 © Anselm Spoerri InfoCrystal

35 © Anselm Spoerri InfoCrystal

36 © Anselm Spoerri A and C and (not B) A and B and C A and B and (not C) A and (B or C) InfoCrystal

37 © Anselm Spoerri A and (not (B or C)) A and C and (not B) A and B and C B and C and (not A) A and B and (not C) C and (not (A or B)) (not (A or B or C)) B and (not (A or C)) InfoCrystal

38 © Anselm Spoerri Query Formulation – Boolean Power Set  InfoCrystal

39 © Anselm Spoerri Query Formulation – Other Ways to Visualize “Power Set” “Bracket”-visualization [Eibl 1999]

40 © Anselm Spoerri Query Formulation – “Power Set” – NIRVE


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