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RecSys Challenge 2014 Workshop Introduction

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Slides introducing the RecSys 2014 Challenge workshop as presented at the RecSys 2014 conference on Oct 10, in Foster City (CA, USA) by Simon Dooms.

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RecSys Challenge 2014 Workshop Introduction

  1. 1. RecSys Challenge 2014 User Engagement as Evaluation Alan Said, Simon Dooms, Babak Loni, Domonkos Tikk @alansaid, @sidooms, @babak_loni, @domonkostikk @recsyschallenge
  2. 2. Today’s Program Welcome Analysis of the Challenge Presentations (4) Coffee Break Presentations (2) Poster Session Discussion & Closing Remarks ACM RecSys Challenge 2014 2 9:00-9:15 9:15-9:30 9:30-10:30 10:30-11:00 11:00-11:30 11:30-12:15 12:15-12:30
  3. 3. First, About Datasets • In the beginning there was MovieLens Good for analysis, experimentation, simulation, and seed data • Now: old, static, synthetic Less interesting for current day experiments • New dataset to fill the void: MovieTweetings Daily updated dataset of movie ratings extracted from IMDb ratings posted to Twitter Recent movies, growing, natural dataset ACM RecSys Challenge 2014 3
  4. 4. The Challenge • Why stop at ratings? • Tweets have much more information! • Focus on ‘user interaction’ • How can we predict user engagement? How does that benefit recsys? ACM RecSys Challenge 2014 4
  5. 5. MovieTweetings Extended • MovieTweetings dataset + Twitter metadata • +200,000 tweets (1 year, 24 days) ACM RecSys Challenge 2014 5
  6. 6. Some Numbers • 225 teams registered, from 50 countries 6 ACM RecSys Challenge 2014
  7. 7. Some Numbers • The dataset was downloaded 407 times 7 ACM RecSys Challenge 2014 More than the number of teams!
  8. 8. Some Numbers • 236 leaderboard updates by 36 teams • 18 papers submitted • 13 papers accepted • 7 presentations • 7 posters ACM RecSys Challenge 2014 8
  9. 9. RecSys Challenge 2014 Presentations
  10. 10. Leaderboard, The Results ACM RecSys Challenge 2014 10 1 2 3 4 5 6 7 8 9 10 11 12
  11. 11. RecSys Challenge 2014 Poster Session
  12. 12. Discussion • Are some ratings more important than others? • Which external data source was useful? • Which are the important features of the tweets? • What else can we do with this dataset? ACM RecSys Challenge 2014 12

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