ON-DEVICE PRIVATIZATION OF MULTI-PARTY ATTRIBUTION DATA

Embodiments of the disclosed technologies receive first event data associated with a first party application, receive second event data representing a click, in the first party application, on a link to a third party application, receive third event data from the third party application, convert the...

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Bibliographische Detailangaben
Hauptverfasser: Wang, Yajun, Rogers, Ryan M, Pardoe, David, Leung, Man Chun D, Tecco, Ryan T, Ren, Shawn F, Wang, Jing, Liu, Bing, Tandra, Rahul, Ahammad, Parvez
Format: Patent
Sprache:eng
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Zusammenfassung:Embodiments of the disclosed technologies receive first event data associated with a first party application, receive second event data representing a click, in the first party application, on a link to a third party application, receive third event data from the third party application, convert the third event data to a label, map a compressed format of the labeled third event data to the first event data and the second event data to create multi-party attribution data, group multiple instances of the multi-party attribution data into a batch, add noise to the compressed format of the labeled third event data in the batch, and send the noisy batch to a second computing device. A debiasing algorithm can be applied to the noisy batch. The debiased noisy batch can be used to train at least one machine learning model.