Patent ID: 11875590
Assignee: MICROSOFT TECHNOLOGY LICENSING, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A system comprising:
a processor; and
a pre-trained self-supervised language model that was trained with sentence pairs produced by inter-and-intra document sampling from a plurality of documents having variable length, the pre-trained self-supervised language model operative upon execution by the processor to:
calculate a two-staged hierarchical similarity matrix for a first candidate document of a plurality of candidate documents based on per-sentence embeddings representing each sentence in the first candidate document, the two-staged hierarchical similarity matrix comprising a sentence similarity matrix and a paragraph similarity matrix representing contents of the first candidate document;
generate an inferred similarity score using the paragraph similarity matrix for the first candidate document indicating a degree of semantic similarity between the first candidate document and a source document;
rank each document in the plurality of candidate documents based on the inferred similarity score for each document;
generate a recommendation including a subset of candidate document from the plurality of candidate documents based on a rank assigned to each document; and
output the recommendation to a user interface associated with the source document.