5 citations · 6 across the 6 of their papers we have counts for
Showing cs.IRShow all
2 papers · 1 filter
cs.IR2022
How Researchers Could Obtain Quick and Cheap User Feedback on their Algorithms Without Having to Operate their Own Recommender System
Tobias Eichinger, Ananta Lamichhane
The majority of recommendation algorithms are evaluated on the basis of historic benchmark datasets. Evaluation on historic benchmark datasets is quick and cheap to conduct, yet ex…
cs.IR2019★ 1 cited
Collaborating with Users in Proximity for Decentralized Mobile Recommender Systems
Felix Beierle, Tobias Eichinger
Typically, recommender systems from any domain, be it movies, music, restaurants, etc., are organized in a centralized fashion. The service provider holds all the data, biases in t…