A Mechanism for Optimizing Media Recommender Systems

TL;DR

This paper introduces a mechanism for media recommender systems that balances producer reach and consumer utility, achieving an optimal, Pareto-efficient distribution through a cost-based approach and a practical algorithm.

Contribution

It presents a novel mechanism that incorporates overreach costs into content distribution, optimizing consumer utility and producer reach simultaneously.

Findings

Achieves Nash equilibrium between producer and consumer.

Identifies optimal content volume for consumers.

Provides an effective algorithm for content distribution.

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.