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RecSys 2012 Demo (Long)

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RecSys 2012 Demo (Long)

  1. 1. demo: “using ratings to profile your health”@neal_lathiauniversity of cambridge
  2. 2. collect #recsys recommendpreferences
  3. 3. user profiles for health(gastrointestinal app)“review” interaction: ratings, tags,text recommendations as tailored health information personalised vs. global health fact
  4. 4. Research Questions● How can recommender systems be used in (everyday) health domains? ● Prof ling, tracking, being “normal” i● How can recommender systems give tailored information without diagnosing? ● Ethics? False positives? False negatives?
  5. 5. code apphttps://github.com/nlathia/PooReview.Android
  6. 6. mood-based mobile(recommender)sensing + experience samplingpreferences:linking behaviour ~ moods just finished: data collection trial with ~40 participants
  7. 7. (co) locationmovement phone social sensing implicitmic proximity experience sampling explicit
  8. 8. Research Questions● How can we recommend activities based on your mood and sensed context? ● How do sensor patterns ~ moods? ● How can this be measured?
  9. 9. public transport ratings(recommender)“review” interaction: ratings, text“recommendations” as aggregatedrecent ratings
  10. 10. Research Questions● How can the system be bootstrapped? ● Cold-start: f lter bots i social media● How can the system solicit/incentivise contributing ratings?● How can we measure the quality and effect of this information?
  11. 11. www.tubestar.co.uk android app

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