Audience Activity Recommendation Using Stacked-LSTM Based Sequence Learning

Abstract

Recommender systems are used to suggest products to audiences by employing a similarity metric. One of the problem of such systems is that it does not incorporate the context of time. As result, it is not possible to change recommendation as audiences' preferences changes over time. In this paper, we will be presenting a solution based on recurrent neural… (More)
DOI: 10.1145/3055635.3056606

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