Abstract: Systems and methods for generating dynamic interfaces using explore-exploit models is disclosed. A first interface including a first set of content modules selected from a set of candidate content modules is generated and feedback data representative of one or more interactions with the first interface is received. The feedback data includes positive feedback and negative feedback. A set of weights for each content module is generated by a contextual explore-exploit model based on the feedback data. A request for a second interface including a context is received and a set of ranked content modules is selected for the context based on the weights of each of the content modules in the set of candidate content modules. A second interface including a second set of content modules is generated. The second set of content modules includes a predetermined number of top ranked content modules in the set of ranked content modules.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform: determining, by a distributed processing architecture and based on first transaction data of first transactions for first items, first micro-intents; grouping, by the distributed processing architecture, the first micro-intents into clusters; receiving, by a distributed memory architecture, second transaction data of a user transaction from a user interface of an electronic device of a user during a current browsing session of a website; determining, by the distributed processing architecture, one or more second micro-intents; determining, by the distributed processing architecture, that the user is expressing a current micro-intent; and transmitting an instruction to display a user interface element on the user interface of the electronic device. Other embodiments are described.

Abstract: Systems and methods for content selection and presentation are disclosed. Training data including indicating one or more interactions with one or more content elements and associated with one of a plurality of individual contexts is received. A selection model is trained by applying a reinforcement learning mechanism and an individual explore-exploit mechanism. A context for a user is selected by applying the selection model, which is configured to determine an expected future reward value of at least one of the plurality of individual contexts, determine an expected future reward value of a global context based on a past click-through rate, a reward value, and a future click-through rate, and, select the global context or one of the one or more individual contexts based on a comparison of the expected future reward values.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations: determining a personal replenishment cycle for an item of a set of items previously purchased by a user; identifying that the user has stopped purchasing a first item in the set of items; removing the first item from the set of items after identifying that the user has stopped purchasing the first item; and reducing a number of database requests for the set of items previously purchased by the user based on the personal replenishment cycle for the item. Other embodiments are described.

Abstract: Systems and methods for generating dynamic interfaces using explore-exploit models is disclosed. A first interface including a first set of content modules selected from a set of candidate content modules is generated and feedback data representative of one or more interactions with the first interface is received. The feedback data includes positive feedback and negative feedback. A set of weights for each content module is generated by a contextual explore-exploit model based on the feedback data. A request for a second interface including a context is received and a set of ranked content modules is selected for the context based on the weights of each of the content modules in the set of candidate content modules. A second interface including a second set of content modules is generated. The second set of content modules includes a predetermined number of top ranked content modules in the set of ranked content modules.

Abstract: Systems and methods for improving diversification in online item recommendations are disclosed. In some embodiments, a disclosed method includes: receiving, from a computing device, a recommendation request seeking recommendations to be displayed on a webpage of a website to a user; obtaining user session data identifying website activities of users on the website; determining weights of a set of content elements associated with the website based on posterior distributions utilizing the user session data; modifying the weights by at least one predetermined parameter to generate updated weights based on contextual feature data of the set of content elements; generating, from the set of content elements, a ranked list of content elements as recommended content based on the updated weights of the set of content elements; and transmitting, to the computing device, the recommended content in response to the recommendation request.

Abstract: A method including tracking impression response data in response to online impressions of content elements displayed to users of a website. The method also can include performing a classification of the users based on the impression response data. The method additionally can include generating a webpage of the website to comprise a content element selected from among the content elements based on the classification of a user of the users. Other embodiments are described.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: coordinating displaying a personalized list of recommended items on a graphical user interface of a user device of a user; determining a personal replenishment cycle for an item of a set of items previously purchased by the user; increasing available storage space in the one or more non-transitory computer-readable media of the system by removing a first item from the set of items to identify that the user has stopped purchasing the first item; and increasing a network bandwidth of the system by reducing a number of database requests for the set of items previously purchased by the user. Other embodiments are disclosed.

Abstract: A system including one or more processors and one or more non-transitory media storing computer instructions configured to run on the one or more processors and perform: identifying a first sub-population of case individuals from a gross population of the case individuals; presenting first test content to a first test sub-population of the case individuals, the first test content is selected according to a first statistical model; measuring a first test sub-population average feedback metric based on first test content feedback provided from the first test sub-population of the case individuals; determining that the first test sub-population average feedback metric exceeds a first control population average feedback metric of a first control population of the case individuals; and determining that a probability value for a difference between the first test sub-population average feedback metric and the first control population average feedback metric is less than a predetermined significance level value.

Abstract: Systems and methods for content selection and presentation are disclosed. Training data including indicating one or more interactions with one or more content elements and associated with one of a plurality of individual contexts is received. A selection model is trained by applying a reinforcement learning mechanism and an individual explore-exploit mechanism. A context for a user is selected by applying the selection model, which is configured to determine an expected future reward value of at least one of the plurality of individual contexts, determine an expected future reward value of a global context based on a past click-through rate, a reward value, and a future click-through rate, and, select the global context or one of the one or more individual contexts based on a comparison of the expected future reward values.

Abstract: A system and method for content selection and presentation is disclosed. A plurality of content elements configured for presentation in at least one content container is received and one of the plurality of content elements is selected for presentation in the at least one content container. The one of the plurality of content elements is selected by a trained selection model configured to select one of an individual context or a global context. An interface including the selected one of the plurality of content elements is generated.

Abstract: A method including tracking impression response data in response to online impressions of content elements displayed to users of a website. The method also can include performing a classification of the users based on the impression response data. The method additionally can include generating a webpage of the website to comprise a content element selected from among the content elements based on the classification of a user of the users. Other embodiments are described.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: displaying content elements on one or more websites to users; tracking respective impression response data for each impression of a respective content element of the content elements comprising (a) a respective response of a respective user of the users and (b) a respective time of the respective response of the respective user; determining respective weightings of the content elements based on posterior distributions using the respective impression response data, as adjusted by a temporal decay factor, based on the respective times of the respective impression response data for the content elements; and generating a webpage of the one or more web sites to comprise a selected content element based on the respective weighting of the selected content element. Other embodiments are disclosed.

Abstract: A method including tracking impression response data in response to online impressions of content elements displayed to users of a website. The impression response data can include (i) first responses by the users in one or more physical stores in response to the online impressions, and (ii) second responses by the users in the website in response to the online impressions. The method also can include receiving a request from a user of the users to display a webpage of the website. The method additionally can include generating the webpage to include a content element selected from among the content elements based on a classification of the user and the impression response data for the content elements. Other embodiments of related systems and methods are described.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: displaying content elements on one or more websites to users; performing a classification of the users into segments; receiving a request from a first user of the users to display a webpage of the one or more websites; determining an amount of information in a respective posterior distribution of each of the one or more first segments of the segments in which the first user is classified, for each of the content elements based on impression response data; selecting a selected content element from among the content elements based on weightings of the content elements for the one or more first segments; and generating the webpage comprising the selected content element. Other embodiments are disclosed.

Abstract: A system and method for content selection and presentation is disclosed. A system receives a plurality of content elements configured for presentation in at least one content container and selects one of the plurality of content elements for presentation in the at least one content container. The one of the plurality of content elements is selected by a trained selection model configured to use Thompson sampling. An interface including the selected one of the plurality of content elements is generated.

Abstract: A system and method for content selection and presentation is disclosed. A plurality of content elements configured for presentation in at least one content container is received and one of the plurality of content elements is selected for presentation in the at least one content container. The one of the plurality of content elements is selected by a trained selection model configured to select one of an individual context or a global context. An interface including the selected one of the plurality of content elements is generated.

Abstract: A system and method for content selection and presentation is disclosed. A plurality of content elements configured for presentation in at least one content container is received and one of the plurality of content elements is selected for presentation in the at least one content container. The one of the plurality of content elements is selected by a trained selection model configured to select one of an individual context or a global context. An interface including the selected one of the plurality of content elements is generated.

Abstract: A system and method for content selection and presentation is disclosed. A plurality of content elements configured for presentation in at least one content container is received and one of the plurality of content elements is selected for presentation in the at least one content container. The one of the plurality of content elements is selected by a trained selection model based on an optimal impression allocation. An interface is generated that includes the selected one of the plurality of content elements.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors and perform: displaying content elements on one or more websites to users; tracking respective impression response data for each impression of a respective content element of the content elements comprising (a) a respective response of a respective user of the users and (b) a respective time of the respective response of the respective user; determining respective weightings of the content elements based on posterior distributions using the respective impression response data, as adjusted by a temporal decay factor, based on the respective times of the respective impression response data for the content elements; and generating a webpage of the one or more web sites to comprise a selected content element based on the respective weighting of the selected content element. Other embodiments are disclosed.