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Recommender systems usually face the problem of serving the samerecommendations across multiple sessions regardless of whether the user isinterested in them or not, thereby reducing their effectiveness. To addfreshness to the recommended products, we introduce a feedback loop where theset of recommended products in the current session depend on the user'sinteraction with the previously recommended sets. We also describe ways ofaddressing freshness when there is little or even no direct user interaction.We define a metric to quantify freshness by reducing the problem to measuringtemporal diversity.

Feedback-based Approach to Introduce Freshness in Recommendations