Transcript Overview and Detail

Text and Documents 1
CS 7450 - Information Visualization
March 15, 2005
John Stasko
Text is Everywhere
• We use documents as primary information
artifact in our lives
• Our access to documents has grown
tremendously in recent years due to
networking infrastructure
 WWW
 Digital libraries
 ...
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Big Question
• What can information visualization provide
to help users in gathering information
from text and document collections?
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InfoVis Tasks
• Two main tasks that Information
Visualization can assist with in this area
 Enhance a person’s ability to read,
understand and gain knowledge from a
document
 Understand the contents of a document or
collection of documents without reading them
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More Specific Tasks
• Which documents contain text on topic
XYZ?
• Which documents are of interest to me?
• Are there other documents that might be
close enough to be worthwhile?
• What are the main themes of a
document?
• How are certain words or themes
distributed through a document?
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We’re Not Doing...
• Information Retrieval
 Active search process that brings back
particular entities
• InfoVis (on the other hand)
 Perhaps not sure precisely what you’re
looking for
 More of a browsing task
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Challenge
• Text is nominal data
 Does not seem to map to geometric
presentation as easily as ordinal and
quantitative data
• The “Raw data --> Data Table” mapping
now becomes more important
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Simple Taxonomy
Enhanced
presentation
(syntax)
Concepts and
relationships
(semantics)
Single
document
Collection of
documents
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Today
• Focus more on syntactic (enhanced
presentation of a document) issue
 Excentric labeling
 Fluid text
 Document lens
 Tilebars
• Next time: focus more on presentation of
concepts and themes
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What’s wrong with this picture?
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Problem
• Where are the labels?
 Labeling is difficult to do when so many
entities exist
 Can add to ball of string problem
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Objectives
• Each label for a data point should:
 Be readable
 Non-ambiguously relate to its graphical object
 Not hide other pertinent information
• Completeness (labeling of all objects) is
desired but not always possible
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Two types of techniques
• Static
 Road maps
 Physical presentations
 Used in cartography
• Dynamic
 Interactive data points
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Cartography
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Dynamic Techniques
• Tool tip or “cursor sensitive balloon label”
 SeeIT
• “All or Nothing” technique, zooming (show all
then small enough)
 FilmFinder
• Magic lens, shows labels inside
• Dynamic Sampling, only 1->3 labels shown at
any one time, context
 Chalmers
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Excentric Labeling
Description boxes
containing the name of
the data point
Area of focus
Line and box color
match the color of the
data point
Fekete and Plaisant
CHI ‘99
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Being Excentric
• “Invisible” – Does not appear until user
hovers over data points
• Describes data points using the name field
• Visually connects labels with data points
• Can order labels to indicate graph position
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Different Techniques
• Radial Labeling
 No intersections
 Position does not indicate value
• Vertical Labeling
 Relative vertical position indicates Y value
• Horizontal Labeling
 Relative horizontal position indicates X value
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Demos
• Different examples at
www.cs.umd.edu/hcil/excentric
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Other Issues
• Dealing with long labels
 Just do truncation
• Limiting discontinuities when scanning
 Users “figure it out”
• Facilitating selection of objects
 Right click to lock current label display and
select one
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Problems/Questions
• Still dependent on mouse movement
rather than showing all
• Can more variables per data point be
shown?
• Disorientation is greater when there are
no other cues besides position
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Augmentation
• Previous work augmented visualizations
with helpful text
• How about augmenting text with helpful
text?
• Example: Tell me a little more about what
I’ll get if I follow a hyperlink
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Fluid Text
• Objective: Annotations to text material
that expand on some item of interest
 Example: For hyperlink of a few words,
annotation explains more about it
• Important for deciding whether to follow
• Do not want to clutter up text with more
noise
Zellweger, Chang and Mackinlay
Hypertext ‘98
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Fluid Link
• When user moves mouse cursor over
hyperlink, more explanatory material is
presented
• Gloss - Expanded material presented
• Click on gloss follows link
• Moving away makes it disappear
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Framework
• Visual cue
 Underline of anchor
• Animated transition
 Gloss effects are smooth animations, allowing
viewer to track changes more easily
• Accommodation
 Primary material needs to shift in some way
to make room for gloss
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Accommodation Techniques
• Interline expansion
 Main text takes on tighter line spacing to
make more room for gloss, or main text
moves into margins more
• Margin callout
 Gloss drawn out in margins, pointed to by line
• Textual overlay
 Main text becomes transparent and gloss is
drawn over it
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Show Technique
• Must really see it work to understand it
fully
• Shows examples of different techniques
Video
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Key Points
• Trying to keep main document free of
clutter
• Animation is crucial
• One way where vision of electronic book
seems a positive
• Comments?
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Problem
• Want to view a page of a document but
see context of surrounding text and pages
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Example
Text is too
small to read
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Potential Solutions
Magnifying
lens
Bifocal
display
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Fisheye
view
Perspective
wall
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The Document Lens
• Focus + Context display
• Use 3D to make more effective use of
available screen space
• Certain region of text in focus and
readable, rest is projected onto 3D
pyramid
Robertson and Mackinlay
UIST ‘93
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The Document Lens
Video
(Saw little
last time on
WebBook)
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Features
• Movable, rectangular magnifying lens
 Mouse - x,y
 Space,alt - z
• Truncated viewing pyramid
• Readable highlighted regions
• Effective use of most of the screen space
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Problem
Lens pyramid can
leave viewing frustrum
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So, couple movement of
lens with viewpoint movement
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Application
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Application
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Improving Text Searches
• What’s wrong with the common search?
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What Hearst Thinks is Wrong
• Query responses do not include include:
 How strong the match is
 How frequent each term is
 How each term is distributed in the document
 Overlap between terms
 Length of document
• Document ranking is opaque
• Inability to compare between results
• Input limits term relationships
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TileBars
• Goal
 Minimize time and effort for deciding which
documents to view in detail
• Idea
 Show the role of the query terms in the
retrieved documents, making use of
document structure
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Hearst
CHI ‘95
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TileBars
• Graphical representation of term
distribution and overlap
• Simultaneously indicate:
 Relative document length
 Frequency of term sets in document
 Distribution of term sets with respect to the
document and each other
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Interface
Search terms
Presentation
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Technique
Relative length of document
Two search
terms
Blocks are darkened
according to the frequency
of the term in the
document
Blocks indicate “chunks”
of text, such as
paragraphs
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See It Work
• Video
• TileBar web page with demo
http://elib.cs.berkeley.edu/tilebars/about.html
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Issues
• Horizontal alignment doesn’t match
mental model
• May not be the best solution for web
searches
 Non-linear material
 Images? Java apps?
• Anything else?
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Still to Come
• Visualizing themes and semantics of
document collections
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Reminder
• Project mid-way progress report due on
Thursday
 2 hardcopies
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HWs
• Your views of Grokker & SequoiaView
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Upcoming
• Documents & Text 2
 Reading
Chapter 10
Salton et al
Lin
• Spring Break
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References
• Spence and CMS texts
• All referred to papers
• Fall ‘99 slides
 Lewis
 Kim and Ho
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