Coupang, Corporation

Intuit, Inc.

Xinli Bao

Vinay Verma

Satyavaraprasad Vadlamudi

Tiziano Cembali

Jing Li

Hyun Jung Cho

Neil Jelmert Jorgensen

Michael Rowan Savio

Bharatwaja Namatherdhala

Systems and methods of generating, for display on a graphical user interface (GUI), a personalized advertisement. The systems and methods can include receiving data indicative of initiating a browsing session, aggregating user activity data associated with a user of the application, the user activity data including current session data and/or past session data, applying machine learning on the user activity data to generate one or more excluded products, applying the one or more excluded products to a product database to generate a list of relevant products, ranking, using one or more ranking rules, the list of relevant products to generate a ranked list of relevant products, and sending, to the mobile device, the personalized advertisement including one or more relevant products from the ranked list of relevant products.

Systems and methods for generating a personalized advertisement

Potential client/small business data and specialist profile data for multiple, and in various embodiments, hundreds, thousands, tens of thousands, hundreds of thousands, millions, tens of millions, or even hundreds of millions or more, potential clients/small businesses and specialists are used to train one or more matching models in an offline training environment using machine learning techniques. Once the one or more matching models are trained, the one or more matching models are used in an execution environment to process a given user's data and available specialist data to identify one or more available specialists determined to be a good match for the user. The user is then provided specialist recommendation data listing the matched available specialists and, in some cases, the user is provided one or more communication mechanisms for connecting with matched available specialists selected by the user.

System and method for matching specialists and potential clients

A system for generating adaptive notifications including processors and memories storing instructions that configure the processors to perform operations. The operations may include generating an item list for notifications to a client ID, selecting a first item from the item list for notification, the first item being selected having a highest priority score and a lowest lifecycle timer, encoding a first landing page by encoding a product code and a tracking cookie in a URL configured for redirection to a first webpage by a redirect server, and transmitting a first notification with a payload including the first landing page and a first message. The operations may also include after transmitting the first notification, modifying priority scores and updating lifecycle timers based on determining whether the client device visited the first landing page. Further, the operations may also include selecting a second item from the item list for notification.

Systems and methods for recurrent and adaptive electronic notifications

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Palo Alto, CA, United States of America

Xinli Bao