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neal lathia
finishing PhD @ UCL (London)
        S. Hailes & L. Capra
intern @ Telefonica I+D (Barcelona)
       X. Amatriain & J. M. Pujol
collaborative filtering
statistics
statistics   user modeling
what does the   how do people
 data show?     make decisions?
similarity



                  trust




user modeling

                 reputation
like-
                 minded?

    similarity
                                 friends?

                     trust




user modeling                      experts?
                    reputation
SIGIR '09
1. Get “expert” data

            2. Compare experts and Netflix
            “users”
SIGIR '09
            3. Recommend to users based on
            experts

            4. Evaluate recommendations
experts?      Accuracy




              Top-N Precision
 User Study
experts?      Accuracy
                                    neighbors?


              Top-N Precision
 User Study



                                enthusiasts?
neighbors?


experts?   user




                  enthusiasts?
given:
  a simple, un-tuned, kNN predictor and multiple
                information sources
a problem:
  users are subjective, accuracy varies with source
a problem:
  users are subjective, accuracy varies with source
a promise:
optimal classification of users to best source produces
           incredibly accurate predictions
a promise:
optimal classification of users to best source produces
           incredibly accurate predictions
a question:
      how to classify users to source set?
preliminary attempts:
(supervised/unsupervised) kNN-voting, similarity-based,
   best-fit, decision trees, SVD, linear combinations,

                                      ...unsuccessful
preliminary attempts:
 learning on the features of user profiles (mean, sd,
                  what was rated..)

                                       ...unsuccessful
metrics:
is the overall RMSE improving?
is the precision/recall of the classification improving?
lessons:
 (1) the web is a goldmine of ratings –
 waiting to be harvested
 (2) recommender systems need to
 model how people make decisions
 (3) accuracy is possible without
 tuning
lessons:
 (2) recommender systems need to
 model how people make decisions
 (3) accuracy is possible without
 tuning
lessons:
 (3) accuracy is possible without
 tuning:
   ...from rating prediction to user classification
   ...from hybrid predictors to hybrid datasets
thanks
n.lathia@cs.ucl.ac.uk

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IJCAI Workshop Presentation