Sequential prediction learning framework and algorithm
This is the implementation of our paper “Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks“. Dataset To successfully test performance, we created TPIC Dataset, a temporal popularity image collection dataset. Overview Our DTCN contains three main components, from embedding, learning to predicting. With a joint embedding network, we obtain a unified deep representation of multi-modal user-post data in a common embedding space. Then, based on the embedded data sequence over time, temporal context learning attempts to recurrently […]
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