661 research outputs found
A Topic Modeling Approach to Ranking
We propose a topic modeling approach to the prediction of preferences in
pairwise comparisons. We develop a new generative model for pairwise
comparisons that accounts for multiple shared latent rankings that are
prevalent in a population of users. This new model also captures inconsistent
user behavior in a natural way. We show how the estimation of latent rankings
in the new generative model can be formally reduced to the estimation of topics
in a statistically equivalent topic modeling problem. We leverage recent
advances in the topic modeling literature to develop an algorithm that can
learn shared latent rankings with provable consistency as well as sample and
computational complexity guarantees. We demonstrate that the new approach is
empirically competitive with the current state-of-the-art approaches in
predicting preferences on some semi-synthetic and real world datasets
- …