Michael Ekstrand

Other Recommender Research

In addition to the various recommender systems projects I lead, I have also been involved in several side projects with other collaborators.

Surveys and Position Papers

I have written or co-authored a few general recommender system papers, including our survey for Foundations and Trends in HCI:

And position papers on recommender systems research and development, either generally or applied to particular areas:

Additional position papers can be found under Reproducible Research.

Rating Interfaces

In this project, led by Tien Nguyen and Daniel Kluver, we examined different interfaces for improving the process of rating movies by giving the user additional information to help guide their rating. We tried several things:

  • Showing the user tags related to the movie, to help them recall its characteristics.
  • Movies similar to the movie to rate for each of the valid rating values, to provide the user with a point of reference.
  • Combining these two interfaces.

The result was published in RecSys 2013.

Information Content of Ratings

In this project, led by Daniel Kluver and Tien Nguyen, we attempt to quantify how much information (in the Shannon information theory sense) is contained in a rating of a movie, and use this as the basis for comparing different rating interfaces based on their efficiency (bits per second).

One of the particularly fun developments in this paper is an experimental protocol for estimating a lower bound on the mutual information between ratings and the preference constructs the user's brain, allowing us to reason about the amount of information about preference, not just information, is in a rating. Unfortunately, this protocol requires a ridiculous number of users to achieve any kind of power, but it's a very nice theoretical development in my opinion.

Database-Embedded Recommenders

This project, led by Justin Levandoski, embedded recommender technology into an SQL database.