The words in a text are averaged to produce an embedding of the text, and hashtags are ranked by similarity to the text embedding.
the model is of the form: where the post w is represented as a bag of words (a sparse vector in R N ), the tag is a one-hot-vector in R N , and U and V are k × N embedding matrices.