公开(公告)号：US20240232936A1

公开(公告)日：2024-07-11

申请号：US18009293

申请日：2022-08-09

Applicant: Google LLC

Inventor： Francesco Nerieri ,  Di-Fa Chang ,  Lan Huang ,  Xinlong Bao

IPC: G06Q30/0242

CPC classification number: G06Q30/0244

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining attributions for unattributed outcomes across different content channels. The method includes receiving, by a model orchestrator, outcome data representing a set of unattributed outcomes, where each unattributed outcome does not have an observed attribution to an exposure of a set of predetermined exposures. The attribution data representing a set of modeled attributions from each outcome model of a plurality of outcome models are received by the model orchestrator, where each set of modeled attribution includes a respective measure between one or more unattributed outcomes and one or more exposures. The respective measures are updated based on one or more criteria for determining one or more updated attributions, where each updated attribution indicates a new attribution of a respective outcome from the set of unattributed outcomes to a corresponding exposure of the set of predetermined exposures.

公开(公告)号：US20240305534A1

公开(公告)日：2024-09-12

申请号：US18009487

申请日：2022-09-09

Applicant: Google LLC

Inventor： Ali Nasiri Amini ,  Zheng Zhao ,  Di-Fa Chang

IPC: H04L41/14

CPC classification number: H04L41/145

Abstract: In an example aspect, the present disclosure provides for an example method including obtaining session data descriptive of one or more user sessions in the networked environment; initializing a mixed effects model configured to describe a first effect and a second effect on a distribution of the session data; optimizing a weighted objective over a plurality of subsets of the session data, the weighted objective comprising a weighting parameter configured to adjust, respectively for the plurality of subsets of the session data, a contribution of the second effect with respect to the first effect; and updating the mixed effects model based on the optimized weighted objective.