US 12,148,003 B2
Systems and methods of providing enhanced contextual intelligent information
Srujana Kaddevarmuth, Cupertino, CA (US); Denila B. Philip, Leonia, NJ (US); Amlan J. Das, Bangalore (IN); Debanjana Banerjee, Bangalore (IN); Apurva Sinha, Fremont, CA (US); Abin Abraham, Bangalore (IN); and Mark A. Hardy, Warren, NJ (US)
Assigned to Walmart Apollo, LLC, Bentonville, AR (US)
Filed by Walmart Apollo, LLC, Bentonville, AR (US)
Filed on Dec. 1, 2021, as Appl. No. 17/540,101.
Prior Publication US 2023/0169540 A1, Jun. 1, 2023
Int. Cl. G06Q 30/0251 (2023.01); G06F 8/41 (2018.01); G06F 21/62 (2013.01); G06Q 30/0242 (2023.01)
CPC G06Q 30/0256 (2013.01) [G06F 8/43 (2013.01); G06F 21/6263 (2013.01); G06Q 30/0242 (2013.01)] 19 Claims
OG exemplary drawing
 
1. A system providing contextual information comprising:
an intent mining system comprising a mining evaluation processor configured to receive inquiry content each associated with different intended recipients and that does not include personal identification information (PII) of the respective intended recipient and does not include personal network cookie data associated with the respective intended recipient, and for each inquiry content associated with a respective one of the intended recipients the mining evaluation processor is configured to:
determine an estimated intent information being sought by the respective intended recipient based on associations with the inquiry content, and identify based on the intent information a mapping to a sub-set of supplemental keywords corresponding to the intent information and having a threshold relationship with the inquiry content; and
identify historic inquiries that are associated with actual historic product purchases and that have threshold relationships with the inquiry content and the sub-set of supplemental keywords and obtain a listing of products that were historically purchased in relation to the historic inquiries;
a product association system comprising one or more association processors configured to, for each inquiry content: evaluate retail product association data and identify a set of multiple products that each have a purchase threshold relationship with one or more products from the determined listing of products, and generate an enhanced listing of products comprising the listing of products and the set of multiple products;
a topic extraction system comprising one or more topic extraction processors configured to: evaluate associations between product parameters of the products of the enhanced listing of products to identify multiple associated topics that are estimated to be relevant to the inquiry content;
wherein the topic extraction system comprises topic extraction machine learning model that has been trained using a topics training corpus of product information and retrained over time based on responses to previous inquiries by previous recipients; and
wherein the topic extraction system in identifying the multiple associated topics supplies the product parameters of the products of the enhanced listing of products to the topic extraction machine learning model to identify the multiple associated topics; and
a distribution system comprising one or more distribution processors configured to: communicate, over an external computer network, the multiple associated topics to one or more target content sources.