Amazon Technologies, Inc.

Fmr Corp.

Akshay Jain

Serdar Kadioglu

Alex Arias-Vargas

Shishir Shekhar

Bernard Kleynhans

Debalina Gupta

Nitin Kumar Grover

Methods and apparatuses are described for automated predictive product recommendations using reinforcement learning. A server captures historical activity data associated with a plurality of users. The server generates a context vector for each user, the context vector comprising a multidimensional array corresponding to historical activity data. The server transforms each context vector into a context embedding. The server assigns each context embedding to an embedding cluster. The server determines, for each context embedding, (i) an overall likelihood of successful attempt and (ii) an incremental likelihood of success associated products available for recommendation. The server calculates, for each context embedding, an incremental income value associated with each of the likelihoods of success. The server aggregates (i) the overall likelihood of successful attempt, (ii) the likelihoods of success, and (iii) the incremental income values into a recommendation matrix. The server generates instructions to recommend products based upon the recommendation matrix.

Automated predictive product recommendations using reinforcement learning

This disclosure describes, in part, a system and process that allows for the automated review of a submitted application to determine the actually requested permissions and identify differences between the requested permissions and a submitted permissions list associated with the application. For example, when an application is submitted for review or approval it may include a submitted permissions list identifying the permissions that are to be associated with the application. In some instances, the permissions included in the submitted permissions list may not correspond with the permissions actually needed for proper operation of the application&#x2014;there may be omitted permissions that should be included and/or permissions included in the permissions list that are never requested by the application. This disclosure describes, in part, a system and process for confirming that the appropriate permissions are included in the submitted permissions list.

Automated determination of application permissions

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New Delhi, India

Akshay Jain