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 userβs perception of the recommendations and the ability of the recommender to meet their information needs.
- RecSys152015
2015. Letting Users Choose Recommender Algorithms: An Experimental Study. In Proceedings of the 9th ACM Conference on Recommender Systems (RecSys β15). ACM. Proc. RecSys β15. DOI 10.1145/2792838.2800195. Acceptance rate: 21%. Cited 96 times. Cited 108 times.
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2014. Towards Recommender Engineering: Tools and Experiments in Recommender Differences.
.Ph.D thesis, University of Minnesota.