  In this paper we present a method to concatenate patent claims to their own
description. By applying this method, BERT trains suitable descriptions for
claims. Such a trained BERT (claim-to-description- BERT) could be able to
identify novelty relevant descriptions for patents. In addition, we introduce a
new scoring scheme, relevance scoring or novelty scoring, to process the output
of BERT in a meaningful way. We tested the method on patent applications by
training BERT on the first claims of patents and corresponding descriptions.
BERT's output has been processed according to the relevance score and the
results compared with the cited X documents in the search reports. The test
showed that BERT has scored some of the cited X documents as highly relevant.
