Chris Noessel > Masters Project: Free Range Learning Support> Real-time Links
Introduction  |  Process  |  The Service  |  Experience Prototypes  |  Conclusion  |  Appendices

Real-time Links

  Flavia Sparacino of MIT's Media Lab demonstrated in 2002 how user preferences could be derived from user behavior in a learning environment. Using the same Bayesian network model, the service could integrate with the computer systems of partner libraries, museums, and even video rental stores to derive the learning interests of customers. Then, on checkout, the system could instantly include free information on the receipt about further local learning resources for the topic, with a URL for further information about the service.

Description of Use

References and Influences:

  • Predictive Networks: Predictive Netowrks has developed a set of "relevance-based navigation tools" that leverage custom behavioral profiling and guidance technologies. Predicitve is another example of a successful algorithm for deriving user preferences by observing their behaviors.

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