Invention Grant
- Patent Title: Transformer-based encoding incorporating metadata
-
Application No.: US17308575Application Date: 2021-05-05
-
Publication No.: US11893346B2Publication Date: 2024-02-06
- Inventor: Hui Wan , Xiaodong Cui , Luis A. Lastras-Montano
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agency: Garg Law Firm, PLLC
- Agent Rakesh Garg; Peter Edwards
- Main IPC: G06F40/284
- IPC: G06F40/284 ; G06F40/205 ; G06F40/30 ; G06F40/42 ; G06F40/237 ; G06V30/194

Abstract:
From metadata of a corpus of natural language text documents, a relativity matrix is constructed, a row-column intersection in the relativity matrix corresponding to a relationship between two instances of a type of metadata. An encoder model is trained, generating a trained encoder model, to compute an embedding corresponding to a token of a natural language text document within the corpus and the relativity matrix, the encoder model comprising a first encoder layer, the first encoder layer comprising a token embedding portion, a relativity embedding portion, a token self-attention portion, a metadata self-attention portion, and a fusion portion, the training comprising adjusting a set of parameters of the encoder model.
Public/Granted literature
- US20220358288A1 TRANSFORMER-BASED ENCODING INCORPORATING METADATA Public/Granted day:2022-11-10
Information query