Abstract ▼ AI-Helper

Recommender system is a core component of e-commerce. Correspondingly, metrics to evaluate the system performance have been developed and applied. However, even though we have lots of applications that have tried to adopt recommender systems, the dearth of successfully installed recommender systems ...

Recommender system is a core component of e-commerce. Correspondingly, metrics to evaluate the system performance have been developed and applied. However, even though we have lots of applications that have tried to adopt recommender systems, the dearth of successfully installed recommender systems for more than a decade leads us to a skeptical thinking that current metrics do not sufficiently indicate the recommender system success in business viability point of view. Hence, the purpose of this paper is to reconfigure measures for recommender system success. Adopting DeLone and McLean's amended model of information system success as the underlying framework, content analysis with intellectual properties on recommender systems was conducted to modify the currently used metrics. Then a model of recommender system success is proposed based on the newly identified metrics are compared with traditional metrics.

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