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AssigneeVectra AI, Inc.
InventorsDaniel Carlton Hannah, Himanshu Mhatre, Sohrob Kazerounian, Timothy John Wade, Karl Lynn, Stephen Malone
Estimating the term…
Disclosed is an improved approach for translating entity prioritization rules to a continuous numerical space. In some embodiments, the approach provided is a system for using qualitative prioritization criteria to train a system that generates quantitative urgency scores for entities. In some embodiments, this comprises an embedding scheme that enables the translation of entity information and their related alerts to a set of qualitative labels based on at least quantitative information. Generally, the system includes a set of analyst actions that establish desired mappings which are used to train a more general model that maps entity embeddings to responses. In some embodiments, the approach comprises one or more models that receive an entity embedding as an input and outputs a score that characterizes the urgency of the response warranted for that entity. In some embodiments, this is performed using various features (e.g., importance, actor type, velocity, and breadth).
A method for translating entity prioritization rules to a continuous numerical space, comprising:
A non-transitory computer readable medium having stored thereon a set of instructions, the set of instructions, when executed by a processor, causing a set of acts or translating entity prioritization rules to a continuous numerical space, the set of acts comprising:
A computing system for translating entity prioritization rules to a continuous numerical space comprising:
Dependencies are inferred from the claim text.