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Each historical action of participant $u_n$ is generated by element-wise plus on content embedding, time embedding and positional embedding. Then, We feed all action embeddings to the multi-head temporal evolving attention layer. The influence of interests at different historical stages on users' current forwarding action is inconsistent. Generally speaking, the closer the timestamp $\tau_n^k$ of message $m_n^k$ is to the current forwarding timestamp $t_n$, the greater the impact. Thus, we design an power-law evolving process for all historical actions. Thus, all historical actions is aggregated by weighted summation. We concatenate multiple head representation related to one specific user and adopt a linear projection |
IEEE/ICACT20230179 Slide.08
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