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State of RecSys
     Recap of the 2012 ACM Conference on
           Recommender Systems



                                      October 23 2012
@alansaid
                                 RecSys Meetup, Berlin
Background
Workshops etc.
● SIGIR '99, '01
● ECAI '06
● Recommenders Summer School @ Strands '06 "1st RecSys"

ACM Conference on Recommender System
'07 - Minnesota 46%
'08 - Lausanne 31%
'09 - New York 43%     2013 - Hong Kong
'10 - Barcelona 19%
'11 - Chicago 20%
                        October 12 - 16
'12 - Dublin 20%
Background cnt'd
"Break" point - 2006
What?             Who?
8 Workshops       Netflix
4 Tutorials       LinkedIn
      33% industry
2 Keynotes        Foursquare
4 Invited Talks   StumbleUpon
24 Papers         Facebook
21 Posters        Yahoo!
10 Demos          Microsoft
2 Challenges      The Echo Nest
                  Academia
Topics (selection)
Human Factors
                     Optimization, Accuracy, Interaction

Social
Preference
Context
Big Data
                         Rating effort vs. Accuracy
Evaluation               Cremonesi et al.
                         http://dx.doi.org/10.1145/2365952.2365963
Topics
                       Control, Trends, Social Networks/Feeds

Human Factors
Social
Preference
Context
Big Data
                Inspectability and Control in Social Recommenders
Evaluation      Knijnenburg et al.
                http://dx.doi.org/10.1145/2365952.2365966



                http://www.slideshare.net/usabart/inspectability-and-control-in-social-recommenders
Topics
                      Implicit Feedback, Noisy ratings, Ranking


Human Factors
Social
Preference
Context
Big Data
Evaluation
                How Many Bits Per Rating?
                Kluver et al.
                http://dx.doi.org/10.1145/2365952.2365974
                       https://www.dropbox.com/sh/e6l0tmdwrsgyhpi/wXw4GfhcNx/presentation.pdf
Topics                    Cold start, semantic analysis, quality assessment




Human Factors
Social
Preference
Context
Big Data
                                Finding a needle in a haystack of reviews
Evaluation                      Levi et al.
                                http://dx.doi.org/10.1145/2365952.2365977



                http://www.slideshare.net/OssiMokryn/cold-start-context-aware-hotel-recommender-system
Big data, frameworks, algorithms, cost, requirements
                                                                                        @_krisjack
Topics
Human Factors
Social
Preference
Context
             http://www.slideshare.net/KrisJack/mendeley-suggest-engineering-a-personalised-article-recommender-
             system                                                                                      @xamat
Big Data
                                                                       @kamikaze_bhasin
Evaluation                       @plamere

                                     Approaches used and problems faced
Big data, frameworks, algorithms, cost, requirements


Topics
Human Factors
Social
Preference
Context
                                                                                                          @xamat
Big Data
             http://www.slideshare.net/xamat/building-largescale-realworld-recommender-systems-recsys2012-tutorial
Evaluation                          @plamere

                                        Approaches used and problems faced
Big data, frameworks, algorithms, cost, requirements


Topics
Human Factors
Social
Preference
Context
                                                                                          @xamat
Big Data
                                                           @kamikaze_bhasin
Evaluation      http://www.slideshare.net/anmolbhasin/beyond-ratings-andfollowers-recsys-2012




                         Approaches used and problems faced
Big data, frameworks, algorithms, cost, requirements
                                                                                               @_krisjack
Topics             http://www.slideshare.net/KrisJack/mendeley-suggest-engineering-a-personalised-article-recommender-
                   system




Human Factorshttp://www.slideshare.net/xamat/building-largescale-realworld-recommender-systems-recsys2012-tutorial



                       http://www.slideshare.net/anmolbhasin/beyond-ratings-andfollowers-recsys-2012

Social
Preference
Context
                                                                                                            @xamat
Big Data
                                                                             @kamikaze_bhasin
Evaluation                            @plamere

                                          Approaches used and problems faced
                                            http://www.slideshare.net/plamere/ive-got-10-million-songs-in-my-pocket-now-what
Topics          top-n, popularity, user-centricity, experiments


                                                       @ronnyk
Human Factors
                Ranking              Rating prediction
Social
Preference
Context
Big Data
Evaluation      Online Controlled Experiments
                Kohavi
Topics          top-n, popularity, user-centricity, experiments


                                                              @ronnyk
Human Factors
                Ranking                  Rating prediction
Social
Preference
Context
Big Data
Evaluation      Online Controlled Experiments
                Kohavi

                          http://www.exp-platform.com/Pages/2012RecSys.aspx
Popular vs. Unpopular topics
User-centricity   Rating prediction
Ranking           Tagging
Big Data          (Movies)
Real Systems
Live Evaluation
Quality of data
RecSys 2013
Website:
http://recsys.hosting.acm.org

Deadlines:
Probably April 2013
on twitter                                                      @recsyswiki
               @danielequercia                                  Recommender Systems Wiki
               Cambridge                    @xamat
                                            Netflix
   @neal_lathia                 @plamere
   Cambridge                    The Echo Nest              @dtunkelang
                                                           LinkedIn
                   @abellogin
                   UAM



   @usabart
                                    #recsys                          @recsysde
                                                                     German RecSys stuff


   UC Irvine                                                   @peterpawas
                        @elehack                               Pitt.
         @_krisjack     @LenskitRS
         Mendeley                               @zenogantner
                                                @MyMediaLite
                                                                 @alexk_z
  @denisparra                                                    Telefonica R&D
  Pitt.
                           @ocelma
                           Gracenote
Thanks!
Questions?

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State of RecSys: Recap of RecSys 2012

  • 1. State of RecSys Recap of the 2012 ACM Conference on Recommender Systems October 23 2012 @alansaid RecSys Meetup, Berlin
  • 2. Background Workshops etc. ● SIGIR '99, '01 ● ECAI '06 ● Recommenders Summer School @ Strands '06 "1st RecSys" ACM Conference on Recommender System '07 - Minnesota 46% '08 - Lausanne 31% '09 - New York 43% 2013 - Hong Kong '10 - Barcelona 19% '11 - Chicago 20% October 12 - 16 '12 - Dublin 20%
  • 4. What? Who? 8 Workshops Netflix 4 Tutorials LinkedIn 33% industry 2 Keynotes Foursquare 4 Invited Talks StumbleUpon 24 Papers Facebook 21 Posters Yahoo! 10 Demos Microsoft 2 Challenges The Echo Nest Academia
  • 5. Topics (selection) Human Factors Optimization, Accuracy, Interaction Social Preference Context Big Data Rating effort vs. Accuracy Evaluation Cremonesi et al. http://dx.doi.org/10.1145/2365952.2365963
  • 6. Topics Control, Trends, Social Networks/Feeds Human Factors Social Preference Context Big Data Inspectability and Control in Social Recommenders Evaluation Knijnenburg et al. http://dx.doi.org/10.1145/2365952.2365966 http://www.slideshare.net/usabart/inspectability-and-control-in-social-recommenders
  • 7. Topics Implicit Feedback, Noisy ratings, Ranking Human Factors Social Preference Context Big Data Evaluation How Many Bits Per Rating? Kluver et al. http://dx.doi.org/10.1145/2365952.2365974 https://www.dropbox.com/sh/e6l0tmdwrsgyhpi/wXw4GfhcNx/presentation.pdf
  • 8. Topics Cold start, semantic analysis, quality assessment Human Factors Social Preference Context Big Data Finding a needle in a haystack of reviews Evaluation Levi et al. http://dx.doi.org/10.1145/2365952.2365977 http://www.slideshare.net/OssiMokryn/cold-start-context-aware-hotel-recommender-system
  • 9. Big data, frameworks, algorithms, cost, requirements @_krisjack Topics Human Factors Social Preference Context http://www.slideshare.net/KrisJack/mendeley-suggest-engineering-a-personalised-article-recommender- system @xamat Big Data @kamikaze_bhasin Evaluation @plamere Approaches used and problems faced
  • 10. Big data, frameworks, algorithms, cost, requirements Topics Human Factors Social Preference Context @xamat Big Data http://www.slideshare.net/xamat/building-largescale-realworld-recommender-systems-recsys2012-tutorial Evaluation @plamere Approaches used and problems faced
  • 11. Big data, frameworks, algorithms, cost, requirements Topics Human Factors Social Preference Context @xamat Big Data @kamikaze_bhasin Evaluation http://www.slideshare.net/anmolbhasin/beyond-ratings-andfollowers-recsys-2012 Approaches used and problems faced
  • 12. Big data, frameworks, algorithms, cost, requirements @_krisjack Topics http://www.slideshare.net/KrisJack/mendeley-suggest-engineering-a-personalised-article-recommender- system Human Factorshttp://www.slideshare.net/xamat/building-largescale-realworld-recommender-systems-recsys2012-tutorial http://www.slideshare.net/anmolbhasin/beyond-ratings-andfollowers-recsys-2012 Social Preference Context @xamat Big Data @kamikaze_bhasin Evaluation @plamere Approaches used and problems faced http://www.slideshare.net/plamere/ive-got-10-million-songs-in-my-pocket-now-what
  • 13. Topics top-n, popularity, user-centricity, experiments @ronnyk Human Factors Ranking Rating prediction Social Preference Context Big Data Evaluation Online Controlled Experiments Kohavi
  • 14. Topics top-n, popularity, user-centricity, experiments @ronnyk Human Factors Ranking Rating prediction Social Preference Context Big Data Evaluation Online Controlled Experiments Kohavi http://www.exp-platform.com/Pages/2012RecSys.aspx
  • 15. Popular vs. Unpopular topics User-centricity Rating prediction Ranking Tagging Big Data (Movies) Real Systems Live Evaluation Quality of data
  • 17. on twitter @recsyswiki @danielequercia Recommender Systems Wiki Cambridge @xamat Netflix @neal_lathia @plamere Cambridge The Echo Nest @dtunkelang LinkedIn @abellogin UAM @usabart #recsys @recsysde German RecSys stuff UC Irvine @peterpawas @elehack Pitt. @_krisjack @LenskitRS Mendeley @zenogantner @MyMediaLite @alexk_z @denisparra Telefonica R&D Pitt. @ocelma Gracenote