, 1 min read
After Netflix? What next?
The Netflix competition is nearly concluded. We have learned that ensemble methods are the solution for more accuracy.
The recommender system community moves on. Immediate questions come to mind:
- Researchers continue to use the Netflix data set. Will it remain freely available?
- We need to study the effect of a 10% accuracy gain (measured by RMS) on user satisfaction. How do we go about it?
Otherwise, it seems that future research is bound by the available data. Models and theory alone have never had much of an impact on the field. Accordingly, there has been a surge of research on recommender systems using social network sites as a data source. Alas, social data is sparse, heterogeneous and ephemeral. Are all the low-hanging fruits gone?