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

Claim 7:
8. A computer-implemented method comprising:
calculating, using a pre-trained self-supervised language model, 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 indicating a similarity between a sentence from a paragraph in a source document and a sentence in a paragraph of the first candidate document and a paragraph similarity matrix representing contents of the first candidate document, wherein the 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;
generating 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 the source document;
ranking each document in the plurality of candidate documents based on the inferred similarity score for each document;
generating a recommendation including a subset of candidate document from the plurality of candidate documents based on a rank assigned to each document; and
outputting the recommendation to a user interface associated with the source document.