Differences in Recommender Algorithms

In this line of work, I have been trying to understand what is different about the output of various collaborative filtering techniques, particularly as such differences relate to the user’s perception of the recommendations and the ability of the recommender to meet their information needs.

• RecSys15

  2015

  Michael D. Ekstrand, Daniel Kluver, F. Maxwell Harper, and Joseph A. Konstan. 2015. Letting Users Choose Recommender Algorithms: An Experimental Study. In Proceedings of the 9th ACM Conference on Recommender Systems (RecSys ’15). ACM. Proc. RecSys ’15. DOI 10.1145/2792838.2800195. Acceptance rate: 21%. Cited 96 times. Cited 108 times.

• ⸘2014‽

  2014

  Michael D. Ekstrand. 2014. Towards Recommender Engineering: Tools and Experiments in Recommender Differences.

  Ph.D thesis, University of Minnesota.