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KMS & Collaborative Filtering. Why CF in KMS? CF is the first type of application to leverage tacit knowledge People-centric view of data Preferences matter Implicit Explicit Are people just data points? Neo-Taylorism Efficiency over Quality for data collection. Community Centered CF.

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kms collaborative filtering
KMS & Collaborative Filtering
  • Why CF in KMS?
  • CF is the first type of application to leverage tacit knowledge
  • People-centric view of data
  • Preferences matter
    • Implicit
    • Explicit
  • Are people just data points?
    • Neo-Taylorism
    • Efficiency over Quality for data collection
community centered cf
Community Centered CF
  • What is a community?
  • Helping people find new information
  • Mapping community (prefs?)
  • Rating Web pages
  • Recommended Web pages
    • Measuring recommendation quantity?
    • Measuring recommendation use
  • Constant status
community cf
Community CF
  • “Personal relationships are not necessary”
  • What does this miss?
  • If you knew about the user, would that help with thte cold start problem?
  • Advisors
  • Ratings
    • Population wide
    • Advisors
    • Weighted sum
  • How would an organization use this?
phoaks
PHOAKS
  • Wider group of people (anyone?)
  • Usenet news (more text)
  • Link mining for Web resources
  • What counts as a recommendation?
    • More than one mention?
    • Positive & negative?
  • Fair and balanced for a Community
  • How do you rank resources?
    • Weights
    • Topics
social affordance implicit
Social Affordance & Implicit
  • How can you not use ratings?
  • Read wear, clicks, dwell time, chatter
  • Not all resources are as identifiable
    • Granular- Web pages
    • Items - commercial products
  • Web is a shared informaiton space without much sharing
  • How do incent people to contribute?
    • Social norms
    • Rewards
context for implicit ratings
Context for Implicit Ratings
    • Who
    • When
    • What
    • How (discovery)
  • Web Browsing
  • RSS Reading
  • Blog posting
  • Newsgroup- listserv use
active cf
Active CF
  • Classic paper issues
  • Leveraging what others do
  • Finding what is already found?
  • Take advantage of universal publishing
  • How about filtering, without the collaboration?
    • Individual preferences
    • Implicit and Explicit
  • Is “wisdom” being accumulated?
sharing references
Sharing References
  • Pointers
  • Packages of Information
  • General flexibility
  • Private and Public resources and ratings
other systems
Other Systems
  • Fab
  • Tapestry
  • Grassroots
  • Epinions
  • eBay
  • Amazon (lists)
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