Explore option to pass multiple query documents as input

[joel-beck]

The output is still a list of recommended documents. The computational costs during inference increase marginally for additional seen query papers, but more significantly for additional unseen query papers.

The most important aspect of the implementation is that any precomputed data frame is only loaded once into memory and then used for all query documents at once!

The only meaningful way to aggregate scores for all query documents is to first build individual rankings for each query document as usual, then sum the scores up for each feature separately and select the top candidate documents for the combined ranks.

Note that the set of documents with positive scores is now likely greater than 100 for each feature which is not an issue though.