For instance, the word embedding of v j is generated from the topic-word distribution W 2 as: The generated word embeddings can be used for specific applications, such as label prediction.
we firstly represent a new document d n by its document embeddings e(d n ), where e(d n ) is the sum of word embeddings of all words in d n .