Invention Grant
- Patent Title: Document replication based on distributional semantics
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Application No.: US16779214Application Date: 2020-01-31
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Publication No.: US11487709B2Publication Date: 2022-11-01
- Inventor: Tommaso Teofili , Antonio Sanso
- Applicant: ADOBE INC.
- Applicant Address: US CA San Jose
- Assignee: ADOBE INC.
- Current Assignee: ADOBE INC.
- Current Assignee Address: US CA San Jose
- Agency: Shook, Hardy & Bacon, LLP
- Main IPC: G06F16/178
- IPC: G06F16/178 ; H04L67/1095 ; H04L67/1097 ; G06F16/182 ; G06F16/93 ; G06N3/04

Abstract:
Embodiments of the present invention are directed toward systems, methods, and computer storage media for using a neural network language model to identify semantic relationships between file storage specifications for replication requests. By treating file storage specifications (or at least a portion thereof) as “words” in the language model, replication vectors can be determined based on the file storage specifications. Instead of determining the relationship of the file storage specifications based on ordering within a document, the relationship can be based on proximity of the replication requests in a replication session. When a replication request is received from a user, the replication vectors can be used to determine a semantic similarity between the received replication request and one or more additional replication requests.
Public/Granted literature
- US20200167317A1 DOCUMENT REPLICATION BASED ON DISTRIBUTIONAL SEMANTICS Public/Granted day:2020-05-28
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