CS 160: Lecture 24

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CS 160 Lecture 24

• Professor John Canny
• Fall 2001
• Nov 29, 2001

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Review

• What is the difference between late and early
  fusion in MM interfaces?
• Give an example of each.
• List some input modes and their advantages and
  weaknesses.

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Multimodal Interfaces

• The OAI model (lecture 20) was our starting point
  for information organization.

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Information Tasks

• Specific Fact-finding
• Find the phone number of Bill Clinton
• Extended Fact-finding
• What kinds of music is Sony publishing?
• Open-ended browsing
• Is there new work on voice recognition in Japan?
• Exploration of availability
• What genealogy information is at the National
  Archives?

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Database queries

• Query languages like SQL are widely used, but are
  hard to learn and easy to make mistakes with.
• SELECT DOCUMENT FROM JOURNAL-DB
• WHERE (DATE gt 1994 AND DATE lt 1997)
• AND (LANGUAGE ENGLISH OR FRENCH)
• AND (PUBLISHER ASIS OR HFES OR ACM)

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Visual Query Builders
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QBE Query By Example

• User chooses a record (Database) or document
  (search engine) and specifies more like this.
• User can also pick a segment of text, even a
  paragraph, from a good document and use it as a
  search query (search engines only).

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Visualizing Search Results
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Multidimensional Scaling
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Multidimensional Scaling

• Multi-Dimensional Scaling (MDS) is a general
  technique for displaying n-dimensional data in
  2D.
• It preserves the notion of nearness, and
  therefore clusters of items in n-dimensions still
  look like clusters on a plot.

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Multidimensional Scaling

• MDS applied to hand-classified discussion topics.

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Multidimensional Scaling

• Clustering of the MDS datapoints (discussion
  topics)

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Multidimensional Scaling

• MDS can be applied to search engine results
  easily because they automatically have a
  high-dimensional representation (used internally
  by the search engine).
• The MDS plot helps organize the data into
  meaningful clusters. You can search either near
  your desired result, or scan for an overview.

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Tasks for a visualization system

1. Overview Get an overview of the collection
2. Zoom Zoom in on items of interest
3. Filter Remove uninteresting items
4. Details on demand Select items and get details
5. Relate View relationships between items
6. History Keep a history of actions for undo,
   replay, refinement
7. Extract Make subcollections

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Visualization principles

• To support tasks 1 2, a general design pattern
  called focuscontext is often used.
• Idea is to have a focal area at high resolution,
  but keep all of the collection at low resolution.
• Mimics the human retina.

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Distortion

• Several visualization systems use distortion to
  allow a focuscontext view.
• Fisheye lenses are an example of strongly
  enlarging the focus while keeping a lot of
  context (sometimes the entire dataset).
• Many of these were developed at Xerox PARC.

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FocusContext Document lens
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FocusContext Webbook lens
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FocusContext Table lens
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Navigation Hyperbolic trees
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Navigation Hyperbolic trees
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Navigation Hyperbolic trees
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Navigation Hyperbolic trees
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Navigation Hyperbolic trees
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Navigation Animation
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Using 3D

• People perceive a 3D world from 2D views, so it
  seems like we could use 3D structure to
  advantage.
• Several systems (also Xerox PARC) have tried
  this.
• Use 3D spatial memory and organization to speed
  up navigation.

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WebBook
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Web Forager
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Representing Hierarchies
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Summary

• High-dimensional data can be visualized by 2D via
  MultiDimensional Scaling.
• FocusContext is a design pattern for showing the
  area of interest and its relationship to the
  entire dataset.
• 3D techniques can leverage the spatial
  capabilities of the human visual system.