summarization (Carenini et al., 2008), and spam filtering (Gee, 2003) all depend on properly representing the content of the message body, which then can be consumed in the target tasks.
for each target user u i , we first identify all others {u j | j =i } that he/she has had communications with, and then bucket the cosine similarity between their embeddings into intervals.