Kms collaborative filtering
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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

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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)


  • Login