Diversity, Serendipity, Novelty, and Coverage
By Marius Kaminskas, Derek G. Bridge. 2016
310 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Information Systems, Management Science and Operations Research
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In Artificial Intelligence
In Information Systems
In Management Science and Operations Research
Citations in the corpus
- How algorithmic confounding in recommendation systems increases homogeneity and decreases utility (2017, background): “It is our hope that this work will help motivate researchers and practitioners to 1) actively assess systems with objectives such as diversity, serendipity, novelty, and coverage [31]; 2) apply causal reasoning techniques to counter the eects of algorithmic confounding; and 3) evaluate the distribut”