Using machine learning to determine job titles based on information pertaining to accesses of data items
AssigneeSequoia Benefits and Insurance Services, LLC
InventorDavid Brian Cook
Life of this patent
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AssigneeSequoia Benefits and Insurance Services, LLC
InventorDavid Brian Cook
Estimating the term…
A machine learning model is trained using information pertaining to accesses of data items at a software-as-a-service (SaaS) management platform. A first training input is generated. The first training input includes access data identifying multiple data items accessed at the SaaS management platform using a subset of user accounts of multiple user accounts associated with a client organization. A first target output is generated. The first target output identifies for each user account, information identifying a respective job title associated with the client organization. The training data is provided to train the machine learning model on (i) a set of training inputs including the first training input, and (ii) a set of target outputs including the first target output.
A method for training a machine learning model using information pertaining to accesses of data items at a software-as-a-service (SaaS) management platform, the method comprising:
A method for using a trained machine learning model using information pertaining to accesses of data items at a software-as-a-Service (SaaS) management platform to determine a job title of a plurality of job titles associated with a client organization, the method comprising:
A system for training a machine learning model using information pertaining to accesses of data items at a software-as-a-service (SaaS) management platform, the system comprising:
A system for using a trained machine learning model using information pertaining to accesses of data items at a software-as-a-service (SaaS) management platform to determine a job title of a plurality of job titles associated with a client organization, the system comprising:
Dependencies are inferred from the claim text.