MACHINE-LEARNING TECHNIQUES APPLIED TO INTERACTION DATA FOR DETERMINING SEQUENTIAL CONTENT AND FACILITATING INTERACTIONS IN ONLINE ENVIRONMENTS

Certain embodiments involve using machine-learning methods to generate a recommendation for sequential content items. A method involves accessing a content item associated with an interaction stage in an online environment. A stage graph, which includes a ratio of interactions, of the content item i...

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Bibliographic Details
Main Authors Chhaya, Niyati Himanshu, Kumbi, Niranjan, Srinivasan, Balaji Vasan, Awatramani, Ajay, Reddy, Sreekanth, Bedmutha, Akangsha
Format Patent
LanguageEnglish
Published 27.10.2022
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
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Summary:Certain embodiments involve using machine-learning methods to generate a recommendation for sequential content items. A method involves accessing a content item associated with an interaction stage in an online environment. A stage graph, which includes a ratio of interactions, of the content item is generated. An additional content item that includes additional stage-transition content is identified. A sequencing function outcome indicating a portion of the ratio of interactions is determined. A transition probability of receiving an interaction with stage-transition content and an additional interaction with the additional stage-transition content is calculated. A content provider system is caused to provide a recipient device with interactive content that includes the additional content item.
Bibliography:Application Number: US202117237892