Document Collections 2

1
Document Collections 2

• cs5984 Information Visualization
• Chris North

2
Approaches

• Clustering (last time)
• Themescapes,
• Network
• Keyword

3

• Clustering
• With
• Full text
• Galaxy of
• News
• pg 452

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Clustering

• Good
• Map of collection
• Major themes and sizes
• Relationships between themes
• Scales up

• Bad
• Where to locate documents with multiple themes?
• Both mountains, between mountains, ?
• Relationships between documents, within
  documents?
• Algorithm becomes (too) critical

5
Network

• Show inter-relationships
• Matrix or Complete Graph
• Similarity measure between all pairs of docs
• Threshold level
• Salton, pg 413

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Variations

• Docs Paragraphs Themes

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Network

• Better for smaller, more detailed map
• Scale up Network visualization
• Good
• Can see more complex relationships between/within
  documents
• Can act like hyperlinks!

• Bad
• Finding specific documents
• Scale up difficult

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Combination Thinkmap

• http//www.thinkmap.com/article.cfm?articleID38

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Keyword

• Search engine, keyword query
• Rank ordered list
• Information Retrieval

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Today

• Hearst, Tilebars, web
• umer, ashwini

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VIBE

• Korfhage, http//www.pitt.edu/korfhage/interface
  s.html
• Documents located between query keywords using
  spring model

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VR-VIBE
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InfoCrystal

• Spoerri, pg 140
• Venn Diagram, all possible combinations
• ABCD
• ACD
• CB
• C

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Keyword

• Good
• Reduces the browsing space
• Map according to users interests

• Bad
• What keywords do I use?
• What about other related documents that dont use
  these keywords?
• No initial overview
• Mega-hit, zero-hit problem

15
Assignment

• Mid-Project status report due today
• Read for Thurs
• Fox, Envision, web, video
• aejaaz, ravi

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Upcoming Weeks

• Im at CHI all next week
• Tues Go to VE, SciViz lab Torg 3050
• Bowman, Kriz, Kelso
• Thurs McCrickard
• Read for Tues Apr 10
• DeFanti, Scientific Visualization, pg 39
• Sayle, Rasmol, web
• Yuying, ?