Patent ID: 11928709
Assignee: WALMART APOLLO, LLC
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. A computer-implemented method comprising:
generating, by a server and based on an exponentially time decayed algorithm, aggregated impression data by monitoring a frequency of display of each of a plurality of elements in one or more prior interfaces over a specified period of time;
generating, by the server and based on an exponentially time decayed algorithm, aggregated engagement data by monitoring a frequency of interaction of each of the plurality of elements in the one or more prior interfaces over a specified period of time;
receiving, from the server at a processor, a search request;
extracting search terms from the search request by applying a natural language processing algorithm to the search request;
identifying at least one search keyword by parsing the search terms;
determining a plurality of campaigns, wherein each of the plurality of campaigns includes data elements representative of at least one item keyword and at least one corresponding item, wherein the plurality of campaigns includes campaigns having at least one item keyword corresponding to the at least one search keyword;
determining an overall engagement probability for each of the plurality of campaigns, wherein the overall engagement probability is determined by:
generating an item engagement probability distribution by a posterior probability distribution of the aggregated impression data and the aggregated engagement data of the at least one corresponding item, wherein the posterior probability distribution is based on a binomial and a beta distribution;
generating, by a machine learning model and based on the item engagement probability distribution, an item engagement probability for the at least one corresponding item of each of the plurality of campaigns, wherein the item engagement probability is determined by a posterior probability distribution of the aggregated impression data and the aggregated engagement data; and
generating the overall engagement probability for each campaign by averaging the item engagement probability for each item of the campaign or selecting a maximum item engagement probability for the at least one corresponding item;

selecting one of the plurality of campaigns having a highest overall engagement probability;
providing output data to the server including the at least one corresponding item for the selected one of the plurality of campaigns;
generating, by the server, an interface including the at least one corresponding item;
providing, by the server, the interface including the at least one corresponding item to a device that generated the search request;
receiving impression data and engagement data for the interface including the at least one corresponding item associated with the selected one of the plurality of campaigns;
generating updated aggregated impression data and updated aggregated engagement data based on the received impression data and engagement data for the interface including the at least one corresponding item associated with the selected one of the plurality of campaigns; and
generating a second interface including at least one second item associated with a second campaign, wherein the second campaign is selected based on an updated overall engagement score of each campaign, wherein the updated overall engagement score is based, at least in part, on updated item engagement probabilities based on the updated aggregated impression data and the updated aggregated engagement data.