Invention Application
- Patent Title: Systems and Methods for Machine-Learned Prediction of Semantic Similarity Between Documents
-
Application No.: US17078569Application Date: 2020-10-23
-
Publication No.: US20220129638A1Publication Date: 2022-04-28
- Inventor: Liu Yang , Marc Najork , Michael Bendersky , Mingyang Zhang , Cheng Li
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Main IPC: G06F40/30
- IPC: G06F40/30 ; G06F40/205 ; G06N3/04 ; G06N3/08

Abstract:
Systems and methods of the present disclosure are directed to a method for predicting semantic similarity between documents. The method can include obtaining a first document and a second document. The method can include parsing the first document into a plurality of first textual blocks and the second document into a plurality of second textual blocks. The method can include processing each of the plurality of first textual blocks and the second textual blocks with a machine-learned semantic document encoding model to obtain a first document encoding and a second document encoding. The method can include determining a similarity metric descriptive of a semantic similarity between the first document and the second document based on the first document encoding and the second document encoding.
Public/Granted literature
- US11694034B2 Systems and methods for machine-learned prediction of semantic similarity between documents Public/Granted day:2023-07-04
Information query