A Mechanism for Optimizing Media Recommender Systems
June 23, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Brian McFadden
arXiv ID
2406.16212
Category
econ.TH
Cross-listed
cs.GT,
cs.IR
Citations
0
Venue
arXiv.org
Last Checked
3 months ago
Abstract
A mechanism is described that addresses the fundamental trade off between media producers who want to increase reach and consumers who provide attention based on the rate of utility received, and where overreach negatively impacts that rate. An optimal solution can be achieved when the media source considers the impact of overreach in a cost function used in determining the optimal distribution of content to maximize individual consumer utility and participation. The result is a Nash equilibrium between producer and consumer that is also Pareto efficient. Comparison with the literature on Recommender systems highlights the advantages of the mechanism, including identifying an optimal content volume for the consumer and improvements for optimizing with multiple objectives. A practical algorithm for generating the optimal distribution for each consumer is provided.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β econ.TH
π
π
The Cartographer
R.I.P.
π»
Ghosted
Measuring the Completeness of Theories
R.I.P.
π»
Ghosted
Interactive coin offerings
R.I.P.
π»
Ghosted
Allocating marketing resources over social networks: A long-term analysis
R.I.P.
π»
Ghosted
Approximately Optimal Mechanism Design
R.I.P.
π»
Ghosted
A Social Network Analysis of Occupational Segregation
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Neural Architecture Search with Reinforcement Learning
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted