Patent ID: 11941691
Assignee: CEREBRI AI INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 19:
20. A method, comprising:
obtaining, with a computer system, one or more out of plurality of datasets having a plurality of interaction-event records, wherein:
the interaction-event records describe respective interaction events,
the interaction-events are interactions in which a first entity has experiences or obtains other information pertaining to second entity, and
at least some of the interaction-event records are associated with respective risks by which sequences of at least some of the interaction events relative to one another are ascertainable;

determining, with the computer system, using a trained machine learning model with a transformer architecture, based on at least some of the interaction-event records, sets of event-risk scores, the sets corresponding to at least some of the interaction events, wherein:
at least some of the event-risk scores are determined at least in part with a machine learning classifier;
at least some respective event-risk scores are indicative of an effective of a respective risk ascribed by the first entity to a respective aspect of the second entity; and
at least some respective event-risk scores are based on both:
respective contributions of respective corresponding events to a subsequent event in the one or more out of the plurality of datasets, and
a risk ascribed to a subsequent event in the one or more out of the plurality of datasets, the subsequent event occurring after the respective corresponding events; and

storing, with the computer system, the sets of event-risk scores in memory.