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AssigneeWalmart Apollo, LLC
InventorsVivek Kaul, Shankara Bhargava Subramanya, Jingsi Zhang
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A system for targeting advertising comprises a processor configured to compute a similarity score between a plurality of customers in a seed set and each of a pool of in-store purchasers having no history of online purchases from the online store of an entity. Each user in the seed set has a history of online purchases from the online store of the entity and a history of in-store purchases from stores of the entity. The processor is configured for selecting a subset of the pool of in-store purchasers having similarity scores above a predetermined threshold. The processor is configured for initiating rendering of advertisements for the online store to the subset of the pool of in-store purchasers.
A system, comprising:
The system of 2, wherein the similarity score is calculated using Jaccard similarity.
The system of 3, wherein the Jaccard similarity is calculated for each of the customer records in the filtered pool of customer records based on a number of items included in purchase records associated with the filtered pool of customer records, without regard to a quantity of each item purchased.
The system of 3, wherein the Jaccard similarity is calculated for each of the customer records in the filtered pool of customer records based on a number of items included in purchase records associated with the filtered pool of customer records and a quantity of each item purchased.
The system of 1, wherein the processor filtering of customer records in the population set to generate the filtered pool of customer records having no purchase records associated with online purchases from the online store further comprises filtering such that each customer record in the filtered pool includes at least one purchase record including at least one item from a selected class of items.
The system of 1, wherein the processor filtering of customer records in the population set to generate the filtered pool of customer records having no purchase records associated with online purchases from the online store further comprises filtering such that each customer record in the filtered pool is associated with a predetermined demographic group.
A method, comprising:
The method of 11, wherein the similarity score is computed using Jaccard similarity.
The method of 12, wherein the Jaccard similarity each of the customer records in the filtered pool is computed based on a number of items included in purchase records associated with the filtered pool of customer records, without regard to a quantity of each item purchased.
The method of 12, wherein the Jaccard similarity each of the customer records in the filtered pool is computed based on a number of items included in purchase records associated with the filtered pool of customer records and a quantity of each item purchased.
The method of 9, wherein filtering, by the processor, customer records in a population set to generate the filtered pool of customer records having no purchase records associated with online purchases from the online store further comprises filtering such that each customer record in the filtered pool includes at least one purchase record including at least one item from a selected class of items.
The method of 9, wherein filtering, by the processor, customer records in a population set to generate the filtered pool of customer records having no purchase records associated with online purchases from the online store further comprises filtering such that each customer record in the filtered pool is associated with a predetermined demographic group.
A non-transitory, machine readable storage medium encoded with program instructions, such that when the program instructions are executed by a processor, the processor performs a method, comprising:
The method of 18, wherein the similarity score is computed using Jaccard similarity, and the Jaccard similarity of each the customer records in the filtered pool is computed based on a number of items included in purchase records associated with the filtered pool of customer records and a quantity of each item purchased.
The system of 18, wherein the processor filtering of customer records in a population set to generate the filtered pool of customer records having no purchase records associated with online purchases from the online store further comprises filtering such that each customer record in the filtered pool includes at least one purchase record including at least one item from a selected class of items.
Dependencies are inferred from the claim text.