I found this post on Gmail's smart compose feature, and it got me thinking about trying to implement it myself.
https://ai.googleblog.com/2018/05/smart-compose-using-neural-networks-to.html
The text is super vague though - the only part that gives any direction at all is "we combined a BoW model with an RNN-LM".
I remember that BoW is an unordered representation of the input corpus where only relative magnitudes are important. But I just don't have enough experience to know how an unordered representation like this could help me predict an ordered suffix.
Does anybody have any thoughts on how this might more specifically work? Or any references for further reading? I wasn't able to find much unfortunately.