Collaborative Filtering

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Collaborative Filtering

• Shaun Kaasten
• CPSC 601.13 CSCW

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Outline

• What is filtering?
• Filtering techniques
• Why should we use CF?
• Examples of CF systems
• Virtual community
• CF design goals
• Evaluation forms
• Active CF
• Summary

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What is Filtering?

• Information overload
• Finding desired information
• Eliminating undesirable

94 Resnick et al.
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Filtering Techniques (in and out)

• Cognitive (content)
• Text in the item
• Economic
• Costs and benefits
• Mass mailings (low production costs)
• Social
• People and judgments
• Collaborative filtering subjective evaluations
  of others

87 Malone et al.
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Why should we use CF?

• People are better at subjective evaluations
• Writing style,clarity, music, cake recipes
• Benefit from seeing the history of an objects
  use
• Read/edit wear

95 Maltz Ehrlich
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Tapestry (1992)

• Xerox PARC
• Users annotate documents they read
• Helped others decide what to read
• Failures
• Not free
• Not distributed
• SQL interface difficult to browse

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Grouplens (1994)
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Bellcore Video CF (1994)

• Suggested Videos for John A. Jamus.
• Your must-see list with predicted ratings
• 7.0 "Alien (1979)"
• 6.5 "Blade Runner"
• 6.2 "Close Encounters Of The Third Kind (1977)"
• Your video categories with average ratings
• 6.7 "Action/Adventure"
• 6.5 "Science Fiction/Fantasy"
• 6.3 "Children/Family"
• The viewing patterns of 243 viewers were
  consulted. Patterns of 7 viewers were found to be
  most similar. Correlation with target viewer
• 0.59 viewer-130 (unlisted_at_merl.com)
• 0.55 bullert,jane r (bullert_at_cc.bellcore.com)

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Bellcore Community Web Browser (1995)
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Movielens (1998?)
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Web CF Amazon Customer Reviews
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Web CF Cnet User Opinions
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Web CF MSDN Article Ratings
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Virtual Community

• Influence each other without interacting
• Share benefits of collaboration without costs
• Time developing personal relationships
• Privacy
• Synchronous communication
• No intelligent agents (other than people)

95 Hill et al.
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CF Design Goals Bellcore Grouplens

• Common
• Easy participation
• People power, not agents
• Prediction accuracy increases with user base size
• Grouplens
• Compatibility
• Privacy
• Rich recommendations
• Bellcore
• Works for groups, not just individuals
• Recommendations should include confidence

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Evaluation Forms

• Explicit
• Music reviews on Amazon
• Grouplens- grading of Usenet message
• Implicit
• Grouplens monitor how long a user reads an
  article

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History-Enriched Digital Objects
94 Hill et al.
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Trade off Effort vs. Rewards
95 Hill et al.
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Finding Similar Tastes

• Compute correlation coefficients for the users
  reviews and others
• Use as weights to combine the ratings for current
  article
• Correlation avoids differences of scale
  interpretation

94 Resnick et al.
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Cold Start Problem

• Profile needed to find similar tastes
• Training period
• No immediate benefit for user (Grudins rule)
• Restricted from new areas

95 Maltz Ehrlich
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Active CF

• Passive
• No direct connection between evaluator reader
• Works for many documents in a single database
• Active
• Intent to share knowledge with particular people
• Works for distributed systems, where just
  finding sources is difficult
• Benefit increases with the divergence of the
  documents

95 Maltz Ehrlich
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Case Study Computer Support Center

• Expectation workers use on-line or printed
  documentation to answer problems
• Finding rely on each other
• Information mediator
• Skilled at finding and applying info

95 Maltz Ehrlich
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Build a system to support

• Collaboration and information sharing amongst
  colleagues
• Information mediators sending out references and
  commentary of useful documents

95 Maltz Ehrlich
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What informal methods are missing

• Contextual information
• Name, source, date, sender information
• Ease of use
• Add annotations
• Return benefits early - no cold start
• Flexibility
• Method of distribution, comments and context
• No set roles

95 Maltz Ehrlich
25
The Pointer System
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Distribution of Pointers

• Private database bookmarks
• Email
• Individuals
• Subscribe-only mailing lists
• Information digests
• Pre-designed document newsletters, reports,
  etc.

95 Maltz Ehrlich
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Challenging Common Theories

• Comment providers should be anonymous
• Knowing something about commenter is critical to
  evaluating the usefulness of that document

95 Maltz Ehrlich
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Challenging Common Theories

• Information finders should be freed from
  addressing and sending mail
• Users really do have recipients in mind when they
  discover information

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Irony of Active CF

• Recipients are passive
• Cannot use system to find reviewed information

95 Maltz Ehrlich
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Summary

• Choice under uncertainty
• Benefit from knowledgeable people
• Virtual community of experts (?)
• Active CF systems help point colleagues to
  information
• Passive CF help explorers learn from the
  community