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Social Recommenders,  Adaptivity, and Feedback       Summary of the Breakout Session from RSSE’12 OhadBarzilay, Lars Heine...
Social Recommenders, Adaptivity, and Feedback1.    Feedback matters.     a)   Feedback to the community (to increase motiv...
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Summary of Breakout Session from RSSE'12

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These slide(s) are the result of our discussion session on social recommenders, adaptivity, and feedback at the RSSE'12.

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Summary of Breakout Session from RSSE'12

  1. 1. Social Recommenders, Adaptivity, and Feedback Summary of the Breakout Session from RSSE’12 OhadBarzilay, Lars Heinemann, Dennis Pagano, Chris Parnin, Luca Ponzanelli, Tobias Roehm, IgorSteinmacher, Margaret-Anne Storey, Giuseppe Valetto, AlexeyZagalsky (in alphabetical order)
  2. 2. Social Recommenders, Adaptivity, and Feedback1. Feedback matters. a) Feedback to the community (to increase motivation) b) Feedback to the system (to increase recommendation quality) c) Both influence each other indirectly. d) Adaptive RSSEs: What gets better – the data or the system?2. People matter. a) Social recommenders build on people and are to be used by people b) When you recommend expert, they also need to have time to spare. Its easier to ask bottom-up in hierarchical organizations3. Trust matters. a) As soon as your data gets used, it depends on where it is used if it is ok for you. b) Trust also applies to whom to believe when recommendations are made (human vs. system)4. Usage Data matters. a) To give relevant recommendations5. New applications: a) Collaborative filtering for features, applications b) Mixing recommendation sources (e.g. stackoverflow, task descriptions) c) Recommenders for which usage data to collect (meta-application) d) Exploit Quick Fix

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