Invention Grant
- Patent Title: System and method for diachronic machine learning architecture
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Application No.: US16875737Application Date: 2020-05-15
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Publication No.: US11694115B2Publication Date: 2023-07-04
- Inventor: Seyed Mehran Kazemi , Rishab Goel
- Applicant: ROYAL BANK OF CANADA
- Applicant Address: CA Toronto
- Assignee: ROYAL BANK OF CANADA
- Current Assignee: ROYAL BANK OF CANADA
- Current Assignee Address: CA Montreal
- Agency: Norton Rose Fulbright Canada LLP
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F16/2458 ; G06N3/00 ; G06N3/086

Abstract:
Systems and methods for expanding a multi-relational data structure tunable for generating a non-linear dataset from a time-dependent query. The systems include a processor and a memory. The memory may store processor-executable instructions that, when executed, configure the processor to: receive the query of the multi-relational data structure, wherein the query includes at least one entity node at a queried time relative to the time data; obtain, based on the query, a temporal representation vector based on a diachronic embedding of the multi-relational data structure, the diachronic embedding based on a combination of a first sub-function associated with a temporal feature and a second sub-function associated with a persistent feature; determine, from the temporal representation vector, at least one time-varied score corresponding to the queried time; and generate a response dataset based on the at least one time-varied score determined from the temporal representation vector.
Information query