A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations
A Dynamic Meta-Learning Model for Time-Sensitive Cold-Start Recommendations
We present a novel dynamic recommendation model that focuses on users who have interactions in the past but turn relatively inactive recently. Making effective recommendations to these time-sensitive cold-start users is critical to maintain the user base of a recommender system. Due to the sparse recent interactions, it is challenging …